Best RFP Software for Enterprise: Top 8 Platforms for 2026

8 Best RFP Software for Enterprise in 2026: At a Glance

What Are Enterprise RFP Platforms?

Enterprise RFP platforms are software solutions designed to help large organizations manage the complexity of responding to RFPs, requests for information (RFIs), and other business proposals. They provide a centralized system for managing content, collaborating with subject matter experts (SMEs), and automating repetitive drafting tasks. The goal is to improve the speed, accuracy, and quality of proposal responses.

Video transcript

Today we're diving into the best AI RFP software that are in the market for 2026. We're gonna be going into the AI agents, the AI workflows, and the AI RFP response process that powers all of these AI RFP software companies. And you're gonna get, at the end of this video, An overview of the best AI native RFP software. Let's jump into it. So first of all, this is a continuation of one of my last videos, which was to do with the best RFP software. So if you wanna have an overall look of RFP software across legacy RFP and AI native RFP, you can have a look at that video which you'll see at the end of the video as well. Link to it below. So what I've analyzed to generate this list of best RFP software is I've looked at the public G2 reviews, the Gartner reviews, and our own industry knowledge, having being an AI-native RFP software ourselves.

So first of all, before jumping into the first one, let's think about the RFP software market as a whole. Effectively, if you're looking for RFP response software, you've got three options. You've got your legacy RFP software. They're like your Loopio, your Responsive, Qvidians. They've been built before AI, and they're effectively a question-and-answer machine. You have your past answers. You get requirements, you upload, and it'll keyword match to find the appropriate answer for those new questions and copy and paste it across. Recently, they've added some more AI features, but they're what we call legacy RFP software, mostly because they've been around for quite a long time and they're not built with a kind of AI architecture to begin with. Then you've got your own AI DIY builds that you can do. Using Claude or ChatGPT or Copilot to effectively help you answer RFPs. And that can be really useful to an extent. And then you'll start to run into issues, especially if you're collaborating across multiple team members, if you're trying to prevent hallucinations and you

wanna get more towards winning responses rather than generic AI responses. You also have your kind of own DIY builds, like doing your own AI agents internally. Then you've got the AI RFP software. These AI native players have been built with AI in mind from day zero, meaning that they're architected for AI and one of the market leaders is AutoRFP.ai.ai, which is where I'm from Okay, there's also the proposal win rate report for 2026. In this report, us and a bid manager community called Stargazy surveyed over a hundred bid managers to find what are those bid teams doing that win the most RFPs, specifically around their tooling, their process, and their systems. What we found, and you can download this report from our website and the link in the description below, is that teams with high content automation and strong processes around customer insights and bringing together all the different data points available to them in RFPs really led to higher win rates.

There's an entire chapter here all around the high-win and low-win cohorts and what matters the most, And there's a whole chapter here on writing winning responses and how teams can get into content automation and do more to win RFPs. So you download that report below. First, let's talk about the best way to evaluate AI RFP software. When looking at AI RFP software, you really wanna make sure you get your hands on the tools. Some of the options I show you today will have access to a free trial directly on their website. Other vendors, you can ask for a proof of concept, like AutoRFP.ai. And with that, effectively, you get access to seeing how the AI will work with your actual RFPs using your actual data. Why that's useful, especially when evaluating AI RFP software side by side, is it lets you see effectively is there proof in the pudding? Does the AI RFP software live up to its claims?

Can it automate RFP response based off my prior content? And does it actually save our team time? let's jump into our first one for the best AI RFP software, and that is AutoRFP.ai.ai. AutoRFP.ai.ai is an AI-native RFP software. It actually launched a few weeks before ChatGPT came out, it's been around for four years, It has customers in over forty-plus countries. Predominantly, it's focusing on technology, so software and hardware and technology services companies, financial services companies, so for instance, asset managers doing DDQs and so on, and healthcare companies like pharmacy benefits managers across the world. And it's used by hundreds customers across the globe to help respond to RFPs. So looking into the platform, you can find out more about their customers and how they use AutoRFP.ai from their website from our website. Our pricing is very transparent.

You can find out on our website. So for instance, the starting price, as well as how to learn more information, so you can get in touch with our team, book an online demonstration where AutoRFP.ai.ai is different and what really sets it apart to be the market leader in the AI RFP software proposal space is really around how it's utilizing agentic features and agents to automate more of the RFP process to help bid managers and proposal writers write winning responses. It's really a lot more about winning RFPs . So if I go to create a project, for instance, you can upload an RFP, Word, Excel, PDF. First what you see here is an AI go, no-go. Before a team will even decide to bid on an RFP, they can make a decision based on AI and their own comprehension of the RFP, Whether it's appropriate to go for, are we a good fit for this RFP? And then the AI will answer each of those different requirements, provide sources and transparency for understanding where that kind of information came from those

RFP documents, and that can help me make a decision whether I want to proceed with this RFP or not Then you've got the AI document importer that will automatically using AI computer vision, scan the document and bring in the necessary response requirement, drop-down cells, and everything like that, include requirement tables, everything that you need to fill out to respond to that RFP then the RFP comes in, and here's the real magic. The AI will search my relevant content in my library, which includes integrations with fifteen plus systems, includes web access. And from that content, it'll use a transparent process to source the correct content through semantic search, through re-ranker models and embedding models, to then bring out the most trustworthy response. Then it'll find the most trustworthy content, and then using AI, generate an appropriate response or take verbatim from my prior answers if required. And as the responses come through, we're greeted with two scores. First, we have our feedback score.

This helps you write better winning responses. It looks at the requirement, it looks at my response, and gives me any feedback to make that response even better, whether it's human written or AI generated. Then you've got the trust score. The trust score transparently displays what information and why that information was used to generate this response. Clicking into here, I can see my exact content that was used to generate the response and why the content was used to generate the response. Then I've got the AI project agent, which you can prompt in natural language, and effectively, you're using this AI across your own content with web search. It can create documents like executive summaries for you. In this example, it's gonna edit these three responses that I've selected following my prompts instructions. While that's happening, I can then look through and make comments. I can select those requirements, and then assign them to my different team members or teams that are working on that RFP As I'm managing this RFP submission, I can quickly go through and see

who has responses left to respond to or what subject matter experts need to approve responses and see how that's going over time. So that's AutoRFP.ai.ai, an AI RFP software. Then you've got Arphie. So Arphie or Arphie.ai is another AI RFP software that has been around for quite a few years. It is predominantly used similar to the others, where you have a content library or knowledge space that has relevant context in terms of your past RFPs. And then it brings all that in to help generate and respond to new RFPs. You can have a look at that website. You can see that the AI is used to manually generate responses. Their integrations and more about their system on their websites. I would say Arphie is generally pretty useful for, mid-market technology companies as well as some large enterprises. Usually would have a strong pre-sales team, sales engineers, solution architects. May not necessarily have a purpose-built bid function and it's useful for

responding to RFPs en masse and so on. They don't appear to have their pricing on their websites. So best bet to get is to get in touch with their team by going to their contact page and yeah, you can get in touch with their team and to understand a bit more about Arphie. Next up is AutoGen. So AutoGen is a little bit different to the others where it's more of what we would call a narrative or long-form RFP software. What that means is AutoRFP.ai, Arphie, what we've discussed so far are used when you wanna upload a bunch of requirements let's say in Excel, Word doc, PDF, and thousand, five hundred, ten thousand responses and generate answers for those. AutoGen may be more useful for architecture, engineering, construction companies and for that it's usually less requirements but usually longer form responses, usually in a Word document. You can find out more about visiting their website Then you've got 1up. 1up has access to a free trial.

Their pricing is transparent, generally useful for teams who are doing a lot of security questionnaires. I would say 1up is actually one of the cheaper systems on the market. Really useful if you're doing like a small number or medium number of RFPs or security questions every year and wanna get started with some basic automation. It's really useful for that, and you can kinda find out more about their website as well there. Then you've got Tribble. Tribble's a little bit different. It's predominantly an extension into Google Sheets or Google Docs like running as a Chrome extension. They do have a platform you can log into and you can find out more about them on their website. It has the proposal automation, so generating responses sales. They're doing more features, around kinda the full cycle of sales. Like you can see there, it has deal prep or follow-up follow-up and they do have transparent pricing. So you can see there it starts at 30 grand USD a year. It starts from 50 per annual projects. So there's a quick overview of each of the AI RFP software. Awesome. You can learn more about AutoRFP.ai at our website, or you can contact each

of the providers we've been through today by going directly to their website and getting in touch with their team. Hope that was helpful thanks

These platforms are essential RevOps tools for organizations that handle a high volume of complex bids, where manual processes involving spreadsheets and documents no longer scale effectively. Product-led teams that need a leaner B2B SaaS RFP software shortlist than the full enterprise set can start there instead.

Pro tip: For teams that want maximum automation without constantly maintaining a traditional response library, AutoRFP.ai stands out. Its self-maintaining library learns from approved answers, documentation, and completed submissions, reducing manual curation while keeping enterprise knowledge governed.

1. AutoRFP.ai: Best for Defensible RFP Automation at Enterprise Scale

AutoRFP.ai is the accuracy-first AI platform for enterprise RFPs, security questionnaires, and DDQs: every answer is source-grounded and citable, with zero library maintenance.

The platform is built for organizations where proposal answers must survive review from security, legal, procurement, compliance, and executive stakeholders. Every response is generated from the enterprise’s winning-response chain, including approved submissions, company documentation, and connected knowledge sources.

Each answer displays the supporting sources, their content age, and a Trust Score showing how well the evidence supports the response. Reviewers can open the exact supporting passage instead of searching through folders or accepting an unexplained draft. When approved content cannot support an answer, AutoRFP.ai flags the gap and routes it to a person rather than inventing information.

This governance model makes AutoRFP.ai particularly suitable for enterprises operating across multiple regions, business units, product lines, and review structures. Sequential approvals, role-based permissions, version histories, audit trails, regional hosting, and private deployment options help organizations scale response automation without removing expert oversight.

Key Features

1. Response Generation

AutoRFP.ai generates submission-ready first drafts from approved content, with final review and sign-off retained by the response team.

Its multi-model pipeline handles retrieval, re-ranking, drafting, redrafting, and checking before the answer reaches a reviewer.

Every answer includes source citations and a Trust Score. The platform also shows content-age signals, helping reviewers identify whether an answer is supported by current documentation or requires closer attention.

Responses follow the company’s established terminology, tone, and structure. Teams can apply win themes and competitive positioning across multiple answers, then use one-click actions to shorten, simplify, rewrite, or polish individual responses.

The Project Agent can also update responses across an RFP, use approved project context, and help create supporting documents such as executive summaries, implementation plans, and compliance matrices.

2. Content Management

AutoRFP.ai connects approved knowledge across SharePoint, Confluence, Google Drive, OneDrive, Notion, Box, Seismic, Intercom, Zendesk, past submissions, and internal documentation.

Semantic search identifies relevant information by meaning rather than depending only on exact wording, tags, or filenames. This helps large organizations find related content even when different departments use different terminology.

Every approved response becomes part of the winning-response chain for future projects. The system automatically categorizes new material and learns from completed work, reducing the need for teams to maintain extensive snippet libraries, folder structures, and taxonomies manually.

Enterprises can still assign content owners, apply review schedules, monitor freshness, and resolve conflicts between outdated and current sources. Zero library maintenance removes repetitive organization work, but it does not remove governance or content review.

3. Collaboration

AutoRFP.ai gives enterprise bid teams one workspace for coordinating proposal managers, sales engineers, security specialists, legal reviewers, product teams, and other subject matter experts.

Editors and reviewers can work on the same response in real time. Requirement-level comments, assignments, sequential reviews, approval histories, and audit trails keep decisions attached to the relevant answer rather than buried in email threads.

Project dashboards show completion status, blocked responses, open comments, upcoming deadlines, and contributor progress. Bid managers can identify bottlenecks and send targeted reminders without maintaining separate tracking spreadsheets.

The Q&A Agent allows employees to ask questions from Slack or Microsoft Teams and receive sourced answers from approved knowledge. Assignments, comments, approvals, and reminders can also reach contributors through Slack, Teams, or email.

4. Integrations

AutoRFP.ai connects with the systems enterprise teams already use for sales, content, communication, identity management, and response delivery.

Salesforce supports RFP intake and project tracking. Content integrations include SharePoint, Confluence, Google Drive, OneDrive, Notion, Box, Seismic, Intercom, and Zendesk. Communication integrations include Slack, Microsoft Teams, and email.

Identity and access options include Okta, Microsoft Entra, Microsoft SSO, Google Workspace, SAML, and SCIM provisioning. The official Model Context Protocol server also gives approved access to enterprise knowledge from ChatGPT, Claude, Microsoft Copilot, and Google Gemini.

Portal Agent helps teams answer questionnaires inside procurement and security portals. AutoRFP.ai can also import complex Word, PDF, and Excel documents, including nested tables, hidden tabs, macros, and compliance fields, then export responses back into the buyer’s original format.

Pricing

Where AutoRFP.ai Shines

• Defensible answer generation: Every answer shows its supporting sources, content age, and Trust Score, giving reviewers a direct way to verify important claims.

• Enterprise governance: Sequential approvals, role-based permissions, version history, audit trails, content ownership, and approval-gated updates support formal review structures.

• Global deployment: Regional hosting in the US, EU, and AU, private deployment options, data sovereignty commitments, and global support help multinational teams meet regional requirements.

• Enterprise security: AutoRFP.ai is ISO 27001 certified and SOC 2 Type II audited, so security review does not have to stall implementation. Customer data is not used to train public machine-learning models.

• Full response workload: RFPs, RFIs, security questionnaires, and DDQs can be managed through one governed platform rather than separate tools and disconnected approval processes.

• Large-team collaboration: Unlimited users allow bid managers to involve subject matter experts, legal teams, security reviewers, product leaders, and executives without creating a seat-management problem.

• Zero library maintenance: Approved responses improve future projects without requiring teams to continuously curate snippets, tags, folders, and taxonomies.

• Format and portal coverage: Enterprises can import complex documents, complete questionnaires inside online portals, and return finished responses in the buyer’s original format.

Where AutoRFP.ai Falls Short

• Buyer-side procurement: AutoRFP.ai is designed for vendors responding to RFPs. It is not an RFP creation, vendor-selection, or procurement-management system.

• Narrative proposal design: Enterprises that mainly produce long-form persuasive tenders, highly designed proposals, or complex desktop-published documents may prefer specialized proposal-authoring software.

• Lowest entry price: AutoRFP.ai is positioned as enterprise response software rather than the least expensive option for small or occasional response teams.

Customer Reviews

AutoRFP.ai holds a strong overall user satisfaction rating on G2 with an average rating of 4.8/5, praised heavily for its efficiency and time-saving automation.

David F., Head of Sales, shared his experience using AutoRFP.ai:

“I love how it takes a dirty Excel file and magically converts it into highly accurate answers. Before AutoRFP, the RFP process was so, so, so painful. I’m not going to lie, RFPs are still challenging, but AutoRFP has removed a lot of the laborious administrative and formatting work.”

Lisa R., Director of Marketing at an enterprise company, said, “I cannot speak highly enough about the AutoRFP platform and the outstanding support I’ve received, especially from Tom, who has been incredibly responsive, patient, and knowledgeable. We recently needed to train 20 NEW users at the last minute, and Tom went above and beyond to accommodate us with a timely and effective training session. His clear communication and deep understanding of the platform made the onboarding process seamless for our team. Why We Love AutoRFP: Time-Saving Powerhouse: Since we started using AutoRFP six months ago, we’ve seen a +50% reduction in the time spent compiling RFP responses. That alone has had a huge impact on our productivity.”

Katie Huff, Sr. Director, Sales Operations at MedeAnalytics, said, “AutoRFP.ai has been one of the most life changing tools that I’ve used in my career.”

Rob Tibbs, Market Principal & Account Executive at Red Rover, said, “It is saving a ton of time and it’s allowing us to respond to more RFPs that we historically wouldn’t have.”

Who AutoRFP.ai Is Best For

AutoRFP.ai is best for enterprises where competitive responses involve multiple departments, strict review requirements, and commercially sensitive information.

• Global enterprise bid teams: Organizations coordinating RFPs across regions, subsidiaries, product lines, and business units.

• Proposal operations leaders: Teams replacing spreadsheets, email chains, or library-heavy legacy platforms with one governed response workflow.

• Regulated organizations: Financial services, healthcare, technology, and other enterprises whose answers may be reviewed by auditors, regulators, security teams, or institutional buyers.

• Large cross-functional teams: Enterprises involving proposal managers, sales engineers, security specialists, legal teams, compliance reviewers, product experts, and executives in the same response.

• Enterprises consolidating tools: Organizations that want RFPs, security questionnaires, and DDQs managed within one platform instead of separate response systems.

• Enterprises considering an internal build: Organizations evaluating ChatGPT, Claude, or another internal response assistant but unwilling to build ingestion, governance, citations, permissions, portal handling, and long-term maintenance themselves.

Video transcript

Did you know the average RFP can take thirty-two hours of manual grueling work? Now, in this video, in under ten minutes, I'm gonna show you how you can use AI RFP automation to drastically reduce the amount of time it takes to get to a first draft for your RFP, DDQ or security questionnaire using AutoRFP.ai. Sick. Let's jump into it. So at AutoRFP, we're an AI RFP software automation platform, across the globe with hundreds of customers using our software every day, battle-tested AI to help you automate RFPs. First, what's the problem? So an RFP or request for proposal or due diligence questionnaire or security questionnaire is a pain felt across all industries, whether it's construction, software, technology, finance, healthcare, anyone selling

to government or private businesses. And these glorified question and answers take hours and hours for people to complete, for them to win new business. It's a crucial part for your business to win enterprise and government contracts, which really help you grow sustainably and quickly. But when you go to bid on one, you are met with the RFP. Average response times are thirty to forty hours, usually involve five to eight people, seventy percent of content is reused but hard to find, and the average win rate across all industries is only forty-three percent. So you're spending hours with uncertainty that you may win, which is where efficiency and writing better responses, leveraging AI helps you win more faster. Now, looking into RFP automation, you have a number of options.

You can pick up a legacy RFP software. They've been around since the late nineties. They brought software to the RFP problem. Effectively, a glorified question and answer bank, like a database. You upload Q&A pairs, and then they try to use keyword matching to find the most relevant to then help you answer questions that you get in your new RFPs and tenders. You can also do AI builds yourself. So you might use ChatGPT or Claude, and you can see our other videos about how you can potentially use them. But effectively, you hit a ceiling where it's hallucinating, it's taking more time now to fix things than it should, and just doesn't have enough context to find the right answer most of the time. Or you can choose an actual AI native leader like AutoRFP.ai. Built from AI from the get go and have built the engine around zero

hallucination, multimodal architecture to leverage the latest models across all your major providers, library-less approach, so it doesn't take a lot of time to maintain the system, really high automation rates and enterprise security built in from day dot. So why do teams choose AutoRFP.ai? The reason is your knowledge is always current. We integrate with over twenty different systems, and we pull in from all your various file management and different software to make sure that your data is always up to date, and you don't have to maintain it across multiple different places. We're most accurate in the category because we leverage the different models, including specialized re-ranker models, embedding models, search models, and your large language models where they're best. And our team of over fifteen software engineers and AI engineers make sure that this is battle-tested, evals are correct, and it produces the correct answer based off your source context. And it's one platform for every stage of the RFP journey, from intake to new RFP

to AI-powered go/no-go to drafting to reviewing and using agents to review and update your RFP response, translation to collaboration across SMEs and different team members, ensuring that they can easily collaborate in an easy-to-use platform, and then exporting as well. Let's start with the AI native auto library. This is the core of the platform where your different content sources and past projects and up- and web scraping all live in the one place and- Any question that comes up, whether it's in an RFP or a team member asking the question, can be automatically answered with trust-based scores, specific semantic search, and ensures that the correct answer is found and used to then answer and generate an appropriate response. Then effectively, you upload a blank RFP.

The AI-powered response engine then automatically generates responses, translates it and everything to have the correct answers. Then your team can very easily edit, review, integrates with Slack and Teams, and everyone's notified on project deadlines. Now, I've spoken enough. Let's jump into the actual product, and you can see AI RFP automation from the start. We start by creating a project, which is a new RFP. We've got our portal agent that can scrape your requirements from web portals like SAP, Ariba and others, automatically ingesting those answers into your AutoRFP.ai instance, and then automatically drafting responses for you to easily enter back into the portal. Or you can upload a zip that contains a PDF, Excel, Word doc of your RFP and import that into the platform.

First we have our AI go, no-go. This ask different questions of your RFP based on your company context to ensure that should we actually bid on this RFP before we start it. It'll automatically grab out key details and link it to our CRM via our integration with Salesforce and so on. And here it's answered each question, and you can see it has confidence levels, it has trust built in, and you can then look back and see where the original source and what, for instance, table or other information. Our AI importer automatically selects every requirement, child requirements, dropdown pick lists response cells, everything else that's required for that RFP. We can manually change it if needed, but it automatically pulls that in. Then we can choose what content from our library or just choose every content, and our intelligent tagging and hierarchy system will make sure that the most relevant content is used for that response. And then I can create my project.

Next, the AI response engine then automatically starts sourcing the correct content from your auto library, re-ranking and finding the most relevant information, using that to then draft, redraft, and edit responses vi- with AI, and then provide those responses back to you in matter of seconds. And you can see here my thirty or so requirements automatically being filled out across the entire project. It's chosen the relevant pick lists, and each one of these have trust scores that I can understand further where this came from. It also has our AI-powered feedback score, and this is where AutoRFP is different to other systems. We don't wanna just help you source the correct answers. We wanna help you write better responses. And this goes into our feedback loop, where as you use the platform and write better responses, the AutoRFP system learns from those responses, and continually, your responses get better to help you win more faster.

Here we can do inline comments, so I can notify my team and so they can jump in, get notifications. I can submit, approve, add attachments, and everything else I can do in this platform. Finally, we have our project overview, which is our project management HQ for this particular RFP, making sure everyone understands deadlines. You can send reminders out to team members and just know when something needs to be completed by and when completed by and who is completing it, making sure that your RFP response is submitted on time and you're not faced with five PM Friday deadlines, calling someone to make sure you can get the correct answer to the correct question that's our short introduction to AutoRFP.ai. There's a lot more in RFP automation and AI RFP software that you can learn but feel free to reach out to our team. We'd love to provide a detailed demonstration to you so you can understand if this is a good fit for your business Already, AutoRFP.ai is in forty-four-plus countries across the globe with hundreds

of customers across different industries like technology, finance, and healthcare, and our customers are winning more faster. One of our customers like Shana Sweeney from SugarCRM won fifteen of their top twenty-five enterprise customers using AutoRFP.ai. They're using AI RFP automation to win more today, and it's a competitive advantage for their businesses. Our pricing is incredibly transparent. You can find more information on our website, to get in touch with our team, head over to our website, AutoRFP.ai. Book in a demo today and learn more and see if we can help you win more faster.

2. Loopio: Best for Established Enterprise Proposal Teams

Loopio is best for enterprises that already have a formal proposal function and want a central system for organizing, reviewing, and reusing approved RFP content.

Its main strength is its mature content-library model. Teams can store approved answers, manage review cycles, collaborate with subject matter experts, and apply audit controls across RFPs, security questionnaires, and DDQs.

Loopio reduces the work involved in maintaining a response library, but it does not remove that responsibility. Enterprises still need clear owners, content categories, review schedules, and processes for deciding which answers remain approved. AutoRFP.ai is the stronger fit when the goal is to reduce manual library curation rather than manage it more efficiently.

Key Features

• Centralized content library: Stores approved answers, supporting documents, and reusable proposal content.

• Response automation: Pulls vetted information from the library to create initial RFP and questionnaire drafts.

• Review workflows: Assigns content owners and schedules reviews for frequently reused answers.

• SME collaboration: Routes questions and approvals to subject matter experts during active projects.

• Governance controls: Supports approvals, auditability, and controlled use of company knowledge.

• Multi-response coverage: Supports RFPs, RFIs, security questionnaires, DDQs, and related proposal work.

Pricing

Where Loopio Shines

• Product maturity: Offers a stable platform with an established enterprise customer base.

• User experience: Provides a clean interface that formal proposal teams can learn relatively quickly.

• Content organization: Gives large teams a structured way to manage extensive collections of reusable answers.

• Review discipline: Helps enterprises assign ownership and establish regular content-review cycles.

Where Loopio Falls Short

• Library setup: Enterprises must organize folders, categories, tags, and reusable content before the system reaches its full value.

• Ongoing curation: Review cycles schedule maintenance but do not eliminate it.

• Content ownership: Libraries can become outdated when responsibility is distributed across business units without a dedicated manager.

• Search dependency: Results can be influenced by how content was originally written, tagged, and categorised.

• Large contributor groups: Organizations should assess how access and licensing work when many occasional SMEs need to participate.

• Source-level verification: Teams should test whether reviewers can inspect the exact supporting passage, content age, and confidence behind each generated answer.

Customer Reviews

Posting on Capterra, a verified reviewer said, “Overall, my experience with Loopio has been great. I love the clean, modern UI and brand that they have. Our team is good at storing questions for future RFPs, so it’s helped us become really efficient and consistent with our responses.”

A Procurement Associate said, “The AI tool within Loopio can use some work. Even if I ask it to be direct or summarize a response, it will still give me a pretty long response with a lot of fluff / unnecessary content.”

Who Loopio Is Best For

• Established proposal departments: Enterprises with formal bid teams and repeatable response processes.

• Dedicated content managers: Organizations with employees responsible for organizing and reviewing reusable answers.

• Library-first workflows: Teams that want their approved content library to remain the centre of the proposal process.

• Mature governance structures: Enterprises with defined ownership, review schedules, and approval requirements.

• Large reusable-content collections: Companies with substantial past-response libraries that can be structured and maintained.

3. Responsive: Best for Complex Enterprise Proposal Operations

Responsive is best for large enterprises that need extensive project management, reporting, content governance, and professional-services support across complex proposal operations.

The platform connects live data, subject matter experts, content, and approval workflows in one system. It also extends beyond standard response drafting into Trust Center, RFQ, procurement, and executive-reporting use cases.

This breadth is useful for organizations with large proposal functions and formal operating models. It can also introduce more configuration, training, and administration than an enterprise needs when the primary goal is governed RFP, security-questionnaire, and DDQ response automation.

Key Features

• Enterprise project management: Coordinates contributors, deadlines, reviews, approvals, and response status.

• Content management: Stores and reuses approved proposal and questionnaire content.

• Reporting and analytics: Tracks workload, team performance, project activity, and response operations.

• Approval workflows: Connects subject matter experts and reviewers through structured processes.

• Trust Center capabilities: Supports sharing security and compliance information with buyers.

• Broader procurement coverage: Extends into RFQs, assessments, and adjacent buyer-side workflows.

• Professional services: Supports more involved enterprise implementations and operating models.

Pricing

Where Responsive Shines

• Project-management depth: Supports large, distributed teams working across multiple concurrent responses.

• Enterprise scale: Fits organizations with complex departments, business units, and approval structures.

• Trust Center functionality: Supports a separate workflow for sharing approved security documentation.

Where Responsive Falls Short

• Implementation weight: Enterprises may require more configuration and process design before the platform is fully adopted.

• Administrative workload: The breadth of the system may require dedicated platform ownership.

• Feature complexity: Smaller or more focused response teams may not need every module or workflow.

• Content maintenance: The response library still requires organization, ownership, and ongoing review.

• Package clarity: Buyers should confirm which capabilities are included in the quoted configuration before comparing total cost.

• Lean-team fit: A focused RFP team may find the system heavier than necessary for recurring questionnaires.

Customer Reviews

Grant N., Sales Engineer, pointed out in a Capterra review that “This allows us to triage important RFPs that often have very tight turnaround times and enables our team to collaborate effectively on responses and handle them swiftly.”

A Bid Manager wrote, “The search algorithm without AI is not as great as it looked during the demonstrations. The auto-respond feature had a lot to be desired. Further, all innovations were sold as an add-on that was priced, which was an issue for budget-constrained teams in getting optimal value.”

Who Responsive Is Best For

• Global proposal operations: Enterprises coordinating large teams across business units and regions.

• Proposal leaders: Managers who need advanced reporting, workload analytics, and executive visibility.

• Complex governance environments: Organizations with formal approval chains and layered review requirements.

• Broad procurement teams: Enterprises managing RFQs, Trust Center activity, and adjacent procurement workflows.

4. Qvidian: Best for Word-Centric Enterprise Proposal Workflows

Qvidian is best for enterprises that produce complex proposal documents and want established content, governance, and Microsoft Office workflows.

The platform combines a central content library, automated questionnaires, professional templates, collaboration tools, and direct access from Word, Excel, and PowerPoint. It is particularly useful for teams that want to continue working inside Microsoft Office while drawing from an approved proposal library.

Qvidian’s longevity and document workflow depth are genuine strengths. Enterprises seeking a more modern, source-traceable response workflow with less library upkeep may find AutoRFP.ai better suited to structured RFPs, security questionnaires, and DDQs.

Key Features

• Microsoft Office integration: Gives users access to proposal content from Word, Excel, and PowerPoint.

• Central content library: Stores approved answers, templates, and reusable proposal material.

• Automated questionnaires: Identifies questions and suggests or inserts relevant responses.

• Document templates: Applies branding, formatting, and style rules across proposals.

• Collaboration workflows: Supports comments, reviews, and distributed proposal teams.

• Excel handling: Supports complex spreadsheets with macros, protected cells, and conditional fields.

• Reporting and governance: Provides controls for formal enterprise proposal operations.

Pricing

• Qvidian’s pricing isn’t publicly listed, so you’ll need to contact Upland’s sales team for a quote.

Where Qvidian Shines

• Microsoft Word fit: Supports proposal writers who complete most of their work inside Office.

• Governance: Provides structured controls for content, reviews, and formal proposal processes.

• Reporting: Gives proposal managers visibility into team and project activity.

• Product longevity: Offers a long market history and an established enterprise footprint.

• Template management: Helps organizations maintain branding and formatting across complex documents.

Where Qvidian Falls Short

• Library administration: The content library must be built, organized, and maintained by the enterprise.

• User experience: Teams moving from newer platforms may find the workflow more complex.

• Implementation effort: Large deployments can require dedicated ownership and process design.

• Pricing visibility: Enterprises must contact the vendor for a tailored quote and configuration.

• Combined workload coverage: Teams managing RFPs, security questionnaires, and DDQs together may prefer a platform centred on that full response workload.

• Answer verification: Source citations, content age, confidence scoring, and abstention are not the central organizing principles of Qvidian’s workflow.

Customer Reviews

Laura Z, a proposal writer, highlighted in a Capterra review that “It has cut down on the amount of time it takes for me to complete searching for RFP responses, which used to be very time-consuming, and streamlines the process for sending questions to SMEs and importing responses.”

Barry T., Client Solutions Sr. Manager, shared that, “Its robust features, like tags, search terms, dividing content into folders, and other flexible features, also make it complicated and not very intuitive. Autosearch tends not to find the best answer and requires further searching. Maintaining content is time-consuming and difficult. Resolving duplicates or similar responses is a slow process.”

Who Qvidian Is Best For

• Word-first proposal teams: Writers who create and edit most submissions inside Microsoft Office.

• Document-heavy enterprises: Organizations producing large, formatted, and template-driven proposals.

• Long-established bid departments: Teams with mature governance and proposal-administration resources.

• Brand-controlled workflows: Enterprises that need professional templates and consistent document styling.

• Formal review structures: Organizations requiring defined roles, approvals, and reporting.

5. Arphie: Best for Modern Enterprise Drafting With Source Citations

Arphie is best for enterprises that want a modern response platform with source citations, confidence indicators, writing controls, and support for broader proposal narratives. For the vs-page on those citations against AutoRFP.ai’s dual scoring, read Arphie compared with AutoRFP.ai.

The platform analyzes RFP requirements, searches connected knowledge sources, and generates drafts with citations and confidence scores. Teams can also control tone, response length, formatting, and other writing preferences.

Arphie is one of the closer alternatives to AutoRFP.ai for source-aware drafting. AutoRFP.ai is the stronger fit when the enterprise requires explicit abstention when approved evidence is missing, deeper DDQ workflows, broader portal coverage, and layered governance for regulated responses.

Key Features

• Source-cited drafting: Shows the supporting materials used to create an answer.

• Confidence indicators: Helps reviewers identify responses that may need closer attention.

• Writing customization: Controls tone, detail level, structure, and formatting.

• Connected knowledge: Pulls information from approved libraries and other connected data sources.

• RFP qualification: Supports earlier assessment of whether opportunities are suitable.

• Competitive research: Helps response teams incorporate positioning and competitor context.

• Narrative support: Extends beyond short questionnaire answers into broader proposal writing.

Pricing

Arphie AI does not publish fixed pricing tiers. Instead, it uses a quote-based “contact us” model, with pricing tailored to factors such as your team’s RFP volume, workflow complexity, and implementation needs.

Although complete pricing plans are not publicly available, Arphie has provided indicative price ranges for its services.

Where Arphie Shines

• Modern interface: Offers a clean experience for proposal, pre-sales, and revenue teams.

• Citation visibility: Gives reviewers supporting sources alongside generated drafts.

• Writing control: Allows enterprises to configure how detailed and formal responses should be.

• Narrative breadth: Supports persuasive proposal sections as well as structured questions.

Where Arphie Falls Short

• Abstention clarity: Enterprises should confirm exactly what happens when approved evidence does not support an answer.

• Approval depth: Large organizations should test whether its review, audit, and permission model matches layered governance policies.

• DDQ specialization: Private-capital and regulated due-diligence workflows are less central to its positioning than general RFP drafting.

• Portal handling: Enterprises completing questionnaires across many procurement and security portals should test coverage directly.

• Regional requirements: Buyers should verify hosting, residency, and deployment options for each region.

• Global support: Large multinational teams should compare available support coverage and implementation resources.

Customer Reviews

A Manager said on Gartner, “Arphie was really easy to set up and get value from immediately. They have an import function to bring in the content library from other legacy RFP tools and it’s really easy to connect with other internal sources to supplement. The whole process took an hour or two to migrate from another system. Once Arphie was set up, answering RFPs through Arphie was like magic. It gave us an awesome first draft for the team to get started on.”

A Senior Associate mentioned on Gartner, “Sometimes there are minor interface bugs but the team fixes them in a matter of hours, if not minutes.”

Who Arphie Is Best For

• Modern enterprise proposal teams: Organizations moving away from older library-led workflows.

• Citation-focused reviewers: Teams that want supporting sources visible beside generated answers.

• Narrative and questionnaire teams: Enterprises handling both structured responses and longer proposal sections.

• Pre-sales organizations: Teams that need configurable drafting and competitive positioning.

6. Conveyor: Best for Enterprise Security Reviews and Trust Centers

Conveyor is best for enterprises whose primary response workload involves security questionnaires, customer trust requests, and controlled sharing of security documentation.

The platform combines questionnaire automation with a Trust Center, browser-based portal completion, cited answers, customer self-service, and document-access workflows. It can also support RFP questions when they overlap with security and compliance.

Conveyor is a strong specialist rather than a general enterprise proposal platform. AutoRFP.ai is better suited to enterprises that want RFPs, security questionnaires, and DDQs managed through one governed response system.

Key Features

• Agentic Trust Center: Lets prospective customers access approved security information and documents.

• Security questionnaire automation: Generates cited responses for recurring customer-security reviews.

• Browser extension: Imports and completes questionnaires inside customer portals.

• Document sharing: Controls access to SOC 2 reports, policies, and other trust documentation.

• Customer self-service: Allows buyers to retrieve information without creating a new manual request.

• Salesforce workflows: Connects trust activity and document access with sales processes.

• RFP support: Answers security and compliance sections within broader RFPs.

Pricing

Where Conveyor Shines

• Security specialization: Provides a workflow designed specifically for InfoSec and customer-trust teams.

• Customer self-service: Can reduce repeated requests for standard security documentation.

• InfoSec credibility: Speaks directly to security-review workflows rather than treating them as a secondary proposal task.

Where Conveyor Falls Short

• Narrower scope: Its main strength is customer security review rather than full enterprise proposal operations.

• DDQ coverage: Investment, insurance, and private-capital DDQs are not a central product focus.

• Proposal strategy: Win themes, broader bid qualification, and narrative proposal management are secondary use cases.

• Cross-functional RFP management: Enterprises may still require another system for non-security proposal sections.

• Governance choice: Buyers should assess how external, live, and connected information is governed before it enters a customer response.

• Original-format round trip: Teams working with complex Word and Excel submissions should test import and export fidelity.

Customer Reviews

Reviewers generally praise Conveyor for saving time, simplifying security questionnaires, and providing responsive support, while some note that its AI can misinterpret questions, respond slowly, and feel clunky or incomplete in certain workflows.

Who Conveyor Is Best For

• Enterprise security teams: Organizations handling a continuous flow of customer security reviews.

• Customer-trust functions: Teams that need both questionnaires and document-sharing workflows.

• SaaS security programmes: Companies regularly asked for SOC 2 reports, policies, and compliance evidence.

• Portal-heavy workflows: Teams completing security questionnaires across browser-based platforms.

• Salesforce-led security reviews: Enterprises that want trust activity connected to the sales process.

• Specialist buyers: Organizations comfortable using a separate platform for broader RFP and DDQ management.

7. Iris: Best for Enterprise and Public-Sector RFP Workflows

Iris, also known as heyiris, is best for enterprises that want sourced RFP drafting combined with a strong public-sector and government-contracting workflow.

The platform generates sourced responses from an organization’s knowledge base and connects with proposal, sales, legal, security, and compliance systems. Its GovSpend partnership also links public-sector opportunity intelligence with response automation.

This public-sector connection gives Iris a clear specialist use case. Commercial enterprises that do not need bid sourcing or government-market intelligence may place more weight on abstention controls, DDQ depth, global scale, and consolidation across response types.

Key Features

• Sourced response generation: Creates drafts from connected enterprise knowledge.

• GovSpend integration: Connects public-sector bid intelligence with the response workflow.

• Compliance workflows: Supports legal, security, accessibility, and governance requirements.

• Content-freshness alerts: Identifies material that may need review or updating.

• Enterprise integrations: Connects with CRM, communication, proposal, and knowledge systems.

• RFP qualification: Helps teams assess opportunities before investing response resources.

• Proposal analytics: Supports visibility into bid activity and response outcomes.

Pricing

• Iris does not publicly disclose a fixed price. It uses quote-based, per-active-user pricing.

Where Iris Shines

• Public-sector buyer fit: Iris is particularly relevant to enterprises pursuing government and public-agency opportunities.

• Earlier opportunity decisions: Its connection to public-sector intelligence can help teams decide where to invest proposal resources.

• Compliance-led workflows: It suits teams that must coordinate legal, accessibility, security, and governance requirements.

• Modernization potential: Iris may appeal to organizations replacing manual public-sector bidding processes with a connected workflow.

Where Iris Falls Short

• Newer market presence: Enterprises may want additional validation of large-scale deployments and long-term product maturity.

• Public-sector emphasis: The GovSpend workflow may add limited value to organizations selling only to private enterprises.

• Freshness management: Alerts identify stale content, but teams should confirm how much updating still requires human action.

• Consolidation: Buyers should test how fully the system handles RFPs, security questionnaires, and DDQs through one governance model.

Customer Reviews

A Director of Sales said on Gartner, “The implementation of Iris has been exceptionally positive, serving as a high-impact solution for the team’s operational needs. It has successfully transitioned my team from manual, time-intensive processes to a more streamlined, automated workflow.”

Another manager at a government, public sector, or education organization with fewer than 5,000 employees said, “The ‘Approved Answer’ tag is applied automatically, even when it is not selected directly. It can also pull in information unrelated to a specific product, although I was shown how to clean this up. The Knowledge Base must be reviewed and updated regularly to ensure the most current information is used.”

Who Iris Is Best For

• Public-sector sales teams: Enterprises pursuing government and public-agency opportunities.

• Compliance-led proposal teams: Organizations with accessibility, legal, and security review requirements.

• Opportunity-sourcing teams: Enterprises that want bid intelligence connected to proposal execution.

• GovSpend users: Companies already using public-sector market data and sourcing workflows.

8. 1up: Best for Lightweight Enterprise Answer Automation

1up is best for enterprises that want a lightweight answer-automation layer for RFPs, DDQs, security questionnaires, and internal product questions.

The platform centralizes selected company sources, generates questionnaire answers, and lets teams retrieve information from tools such as Slack. It is positioned more broadly as a GTM knowledge platform rather than only as proposal-management software.

This broader answer layer can be useful when speed and adoption matter more than formal proposal operations. AutoRFP.ai is the stronger fit when an enterprise needs a governed system of record with layered approvals, audit trails, abstention, and deeper RFP, security-questionnaire, and DDQ workflows.

The enterprise workflow comparison between AutoRFP.ai and 1up.ai checks those differences against each vendor’s current public documentation.

Key Features

• Questionnaire automation: Generates bulk answers for RFPs, DDQs, and security questionnaires.

• Connected knowledge base: Centralizes selected documentation and previous responses.

• Source selection: Lets users choose the content and tags relevant to a questionnaire.

• Slack answers: Gives sales and pre-sales teams access to product knowledge inside their normal workflow.

• Knowledge-gap reporting: Shows what employees ask and where documentation may be incomplete.

Pricing

Where 1up Shines

• Fast setup: Gives teams a relatively direct path from connected documents to usable answers.

• Broad GTM use: Supports internal questions as well as customer-facing questionnaires.

• Transparent pricing: Makes initial evaluation easier for individual departments and smaller deployments.

• Knowledge centralization: Brings scattered product and technical information into one answer layer.

• Questionnaire breadth: Supports RFPs, DDQs, security questionnaires, and compliance forms.

Where 1up Falls Short

• Proposal governance: It is more focused on answer automation than on becoming a full enterprise proposal system.

• Approval workflows: Enterprises with sequential legal, security, and executive reviews may require deeper controls.

• Auditability: Buyers should test whether version history and approval evidence meet formal governance requirements.

• Project management: Large proposal operations may need more detailed assignments, deadlines, dashboards, and workload reporting.

• DDQ specialization: Private-capital and regulated due-diligence workflows are not its main area of differentiation.

Customer Reviews

A Sales Manager wrote on Gartner, “Amazing, extremely intuitive and responsive product. We are able to use the platform or Chrome extension to quickly and easily get our questionnaires loaded. The team is very involved, responsive and loves feedback.”

A Director of International Presales and Bid Management wrote, “(1) There is often an error in the processing of new questionnaires. They’re small errors, but still. (2) Their UI workflow capabilities, up until recently, are limited. (3) Their filtering capabilities are limited.”

Who 1up Is Best For

• Enterprise pre-sales teams: Groups that need quick access to product and technical answers.

• Department-level deployments: Business units testing questionnaire automation before a broader rollout.

• GTM knowledge teams: Organizations that want internal and external answers from the same connected sources.

• Slack-centered teams: Employees who prefer retrieving approved information inside communication tools.

• Lightweight questionnaire workflows: Teams that do not need the full depth of an enterprise proposal-management platform.

How to Choose the Right RFP Tool for Enterprise Teams

Enterprise RFP software should support more than drafting. The right platform should help teams qualify opportunities, coordinate reviewers, manage approved knowledge, reduce risk, and measure the impact of automation.

1. Evaluate the Full RFP Workflow

Start by identifying where your current process slows down, from opportunity qualification and document intake to drafting, review, submission, and reporting.

Look for capabilities such as:

• Accurate answer generation: Creates source-grounded responses from approved enterprise content.

• Low-maintenance content management: Keeps approved knowledge accessible without constant manual library curation.

• Go/No-Go analysis: Helps teams decide whether an opportunity is worth pursuing.

• Enterprise integrations: Connects with CRM, knowledge, communication, and identity-management systems.

• Gap Analysis: Identifies recurring missing or non-compliant requirements across RFPs.

• Project management: Tracks assignments, deadlines, open questions, reviews, and approval status.

• Submission support: Handles complex files and buyer portals while preserving the original format.

• Automation Reporting: Shows how many answers were accepted, edited, or completed manually.

AutoRFP.ai brings these stages together through Go/No-Go Analysis, source-grounded response generation, zero library maintenance, enterprise integrations, Gap Analysis, project management, portal handling, original-format export, RFP reporting, and Automation Reporting.

2. Check How the Software Verifies Its Answers

Enterprise reviewers should be able to see where every answer came from. Look for citations, supporting passages, content-age information, and confidence indicators that make generated responses easier to verify.

Also test what happens when the platform cannot find enough approved information. Stronger systems should flag the gap, leave the answer unresolved, or route it to a subject matter expert rather than generate an unsupported response.

3. Match Governance and Security to Enterprise Risk

Enterprise RFPs often involve confidential, regulated, or commercially sensitive information. Review the platform’s security certifications, hosting options, data-use policies, access controls, version history, approval workflows, and audit trails before choosing based on drafting features alone. Teams in banking, insurance, and investment management should also review our ranked financial services RFP platforms comparison, which weights defensibility, DDQ handling, and audit trails, plus our asset-manager RFP software comparison when LP DDQs dominate the workload. Fintech vendors facing bank security reviews can use the fintech RFP software shortlist for SQ-heavy motions. Carriers comparing proposal and questionnaire tooling side by side can go deeper with our insurance RFP software ranking.

Responsive may suit large enterprises that need deep project management, reporting, and professional-services support. Qvidian may fit established proposal teams that rely heavily on Microsoft Word and formal content-governance processes.

4. Decide How Much Content Maintenance Your Team Can Support

Library-first platforms can work well when an enterprise has dedicated content managers who can organize answers, assign owners, manage review dates, and remove outdated material. Loopio is a strong option for teams that already operate this way.

Other enterprises may prefer a system that uses approved documents and past submissions without requiring constant snippet and folder maintenance. Ask each vendor how new knowledge becomes available, how outdated sources are handled, and how much manual content administration remains after implementation.

5. Test the Platform on a Live Enterprise RFP

A product demonstration cannot show how the software will perform with your content, terminology, reviewers, permissions, and submission requirements. Run a proof of concept using a real RFP with complex questions and multiple approval stages.

Measure:

• Answer quality: How many generated responses can be submitted without edits.

• Source quality: Whether reviewers can open and verify the supporting evidence.

• Risk handling: How missing, outdated, or conflicting information is managed.

• Workflow impact: Whether assignments, reviews, and deadlines remain visible.

• Format fidelity: Whether the final response returns correctly to the original document or portal.

AutoRFP.ai shows the percentage of responses accepted without edits, lightly edited, substantially edited, or completed manually. This gives enterprise teams a practical way to evaluate automation quality and reviewer workload using their own bids.

Future of Enterprise RFP Automation

The future of enterprise RFP automation is not simply generating more content with AI. Winning teams will use automation to remove repetitive work while protecting time for qualification, customer insight, win themes, governance, and final review.

AutoRFP.ai’s 2026 Proposal Win Rate Report surveyed 97 bid professionals, and found that operating structure matters more than response speed alone.

• AI will support strategy, not replace it: AI adoption alone does not predict stronger performance. Enterprises need to combine automation with customer research, approved win themes, and structured decision-making.

• Automation will protect strategic capacity: Repetitive drafting and content retrieval will increasingly be automated, allowing proposal teams to shape the narrative while SMEs validate technical and factual accuracy.

• Governance will become a core requirement: Among the High Win Cohort, 71% used a Go/No-Go qualification step, 65% had formal review and governance, and 53% completed structured pursuit or capture work before the RFP arrived.

• Automation, reuse, and insight will work together: Teams combining content automation, high content reuse, and systematic customer insight were three times less likely to remain in the lowest win-rate bands. Among these teams, 63% reported shortlist rates of 51% or higher, compared with 45% of other teams.

For enterprise buyers, this means choosing RFP software that can verify answers, connect approved knowledge, support qualification and governance, identify content gaps, and report automation impact. Drafting speed will still matter, but accuracy, strategic capacity, and measurable revenue contribution will define the next generation of enterprise RFP automation.

Video transcript

You've just received that monster RFP. It's a lot of work, and you're excited to dive in and potentially win this massive contract. You've started using AI, but how do I actually win? What is the RFP response that I need to write to win this deal? That's what takes from basic level of proposal writing to what wins. I'm Rob from AutoRFP.ai. We're an AI RFP software. I personally complete and win RFPs on the daily, and I'm keen to dive in today about using AI for an RFP response that actually helps you win RFPs. I'm gonna be covering win themes. I'm gonna be covering leveraging customer insights to write strategic narrative that helps you actually win RFPs. Yes, we're gonna be talking about AI automation and saving time,

but it's not just about that. It's not about doing an RFP as fast as possible with as little effort as possible and just putting out slop into the world. It's about writing and winning RFPs. But first, as I did say, it's about RFP automation with AI for our RFP response process. It's about automating the mundane. Before you dive into how you can use AI to help you win RFPs for RFP response, take a step back and think about, what are the activities I do related to RFPs that don't actively help me win RFPs? So automate the mundane. AI's real job in an RFP, isn't to do what you do well and what humans do well, and that is writing strategic narrative. It is to do what it does well, and that is hunting and pecking throughout

your past responses, automating kind of the basic responses and really making sure that those are compliant as Jasper Cooper, our CEO and co-founder at AutoRFP.ai, put in our proposal win rate report for 2026, the real advantage isn't automating content, it's what teams do with the time they get back. So automate as much as you can on the mundane So firstly, these are some clear things you can hand to AI from the start. The clear yes or no. Does your product or service do this? And it has a yes box or a tick box or a radio button or a drop-down selection. Yes, . AI should be completing those 99% of the times. Of course, having a human to review if appropriate, but that is where AI is good, the black and white. Company information all the content forms you get about company legal name, company entity, where the office is based, and so on.

If there isn't a place to kinda put your flair there, of course, just basic information, AI is good for that. Boilerplate. Then you've got boilerplate and your security and compliance questions. Across our customer base, 63% of every AI-generated answer is approved with zero to one-word changes. That is 63% of AI-generated answers are perfect. A human still reviews them, but it doesn't require any manual editing. That's freeing up enormous time for teams using our software and the other software out in the market to then, take that time back to do what wins. So what are those activities you can do to help win? First Automate the answer everyone gives and write the answer only you can give. But first, let's cover off what a great answer looks like, and I'll give you both a good and a bad example. So what does a great answer look like?

And this is subjective, of course, to your industry, to your country your buyer. It's all dependent on so many factors. My background is in technology RFPs. That's where I've spent ten years working and selling and writing RFP responses across local government, national government, state government, as well as private enterprise RFPs in Australia, in the UK, in Europe and it is very subjective what a great answer looks like. But I'm gonna take on a couple of core principles that are gonna help you think about what a great answer looks like for your use case. So leads with the verdict. I'm a big believer in front-running the value of the response in the first sentence or two. What that means is effectively, if we're thinking about how humans read, and especially if your job is to read a handful of RFP responses, it's pretty

hard work to continually stay focused and read an entire response and remember everything that you read in there. You wanna make sure that it's easy for the reader to understand the value in your response, and tick off and give you the points that you need in that evaluation criteria. Second, mirror the buyer's words. This is where your understanding of that industry, of that country, of that buyer goes into how you talk about the response. Three, specific enough, no competitor could paste it. Again, imagine you have an evaluation criteria and you are marking this RFP, and you have two responses that look exactly the same. How are you gonna differentiate? That's where being specific enough no competitor could could paste it is so important to make your response stand out, short and scannable. Now, short is dependent on the type of RFP or RFI that it may be and what they're expecting for responses. Make it scannable. Make it a pleasure to read. Don't make it giant block paragraphs that are incredibly hard, again,

for that evaluator to give you the marks for that response. Make it have bullet points. Make it have flowing paragraphs. Make it have a summary or conclusion at the end if reasonable. Make it short and concise and scannable this is probably the biggest sin I see in executive summaries. Someone writes an executive summary, maybe it's the CEO has the standard template one that they use, and it's all about them. It's all about your company, it's all about your experience, and it's boring to read. Make it about the buyer. Easy way to do this is scan the left margin. How often do the sentences start with we, our, your company's name, and so on? How often is this talking about you? Leverage your customer insights and incorporate it into your win themes to make it about them. Tie your solution into the pain and the problems that they are living, and write about them, not about you. But you're tying everything back into their world because it's just more contextual, and it's easier for them to map your response to the evaluation

criteria and how it meets their stated objectives and goals for the RFP. So this is what a great answer can look like. This answer was actually is using social proof. It's one of our answers that we would write, and effectively it's talking about a migration. So SugarCRM migrated from Qvidian to AutoRFP.ai in 2024 and deployed in two weeks. The first sentence has the value. Social proof time. Because we're thinking about migrations. The buyer might be thinking about how long does that take? What's the risk here? How long does it take is answered in the first sentence, and social proof helps alleviate the risk. Then the next three dot points, again, incredibly skimable and readable and has numbers to draw attention. So this requirement was regarding do you have any customers who have migrated? A forgettable answer. AutoRFP.ai.ai, so leads with me, leads with us. Maintains version control automatically through the History tab. First of all, a lot of flowing commas, a pretty long sentence. We've kinda cut off the response, but it keeps going.

No hook, no numbers no so what for the buyer. And effectively it's correct, and for a functional question in a response, it could be a great response if it was looking for a black-and-white response. So it's a forgettable response. So how would we improve this response? We might say Audibility and traceability is core to the platform. This extends to the history tab in which… and then you might use then dot points to list out all the relevant comma points there. So I'm gonna give you some concrete examples of how you can use AI to incorporate win themes and customer insights to help you write winning RFP responses. First of all, the data. We did a survey of over a hundred winning bid teams and asked them what do they do to win. These are teams that win more than 50% of the RFPs they bid on. 71% of high win teams use win themes, 42% of low win teams use win themes.

So a clear distinction, the difference there. This is a strategic part of your RFP response use your intuition and your knowledge of the buyer, your knowledge of your company and your products and services to really fine-tune it. But it can definitely be helpful in thinking of ideas and going back and forth and helping you once you've generated those win themes, actually deploying the win theme across an RFP response. So the RFP, what you receive from the buyer, often will have a bunch of context about their current situation That is gold to help you understand exactly what to incorporate. Once you have the win themes, then you go into applying win themes everywhere. Try to win th-thread these win themes consistently throughout every section. Flag answers that drift, especially on the answers where it matters. I'm using my project agent here so it's talking about differentiation, and then it has access to the web, it has access to my content library, it has access to my CRM, and it's gone

through and looked at all that in different information and found a bunch of different information relevant to this RFP that I'm currently working on and helped create some win themes. So win themes are, it's a scalable platform. Win theme number two, reduces security and compliance risk. It's easy to use and it's integration flexibility integrates with their entire tech stack. Maybe that is also a point of competitive differentiation. If I understand the market and the competitors really well, potentially my solution might be the only one that has a particular integration with a particular system in the buyer. So I wanna highlight that fact consistently that we have the experience of integrating their entire technology stack to our solution, and that is important because of X, Y, Z, because of what's stated in the RFP, because the buyer has told us or we've spoken to the buyer about it. Okay, so we've got all these different win themes that was created via AI, and now I'm gonna ask it, can you now incorporate these win themes across functions?

The AI is now going to start incorporating the win themes by editing these responses for me, by searching my past content, and effectively giving me a stronger narrative of why this buyer should choose our solution Now, it's generating those responses. I can go through, I can see the changes it made, and I can accept this or not. Okay, cool. That looks good. And then I can go through, and I can look at these responses and accept and change them as well, and make sure it incorporates what I want in the responses as well. Let's try and find one here You can see it keeps using the word configurable. So it's reasserting though that vocabulary that ties to integration strengths of our platform, But that's just an example of how we, how I used AI and the AutoRFP.ai project agent to generate win themes based off the RFP project, based off my knowledge of the buyer. And then from that we work to incorporate four win themes, and

then I've used AI to help apply that. I would then go through and edit and make changes here if necessary. And then we've got a strategic narrative throughout that section on the functional requirements. So what are customer insights? It's not just that we know who the buyer is and we've spoken to them a couple of times, but it's actually understanding their current state. It's about understanding their pain, their problems, why they're looking to go out to market, what has been their history of solutions, and everything we understand about that customer, about industry, about the geography and other relevant customers in the space to, understand their world and help pitch a solution that would generally provide value to them. So where can customer insights live? First of all, in your CRM. There's a goldmine of information in your CRM Then you've got your recorded discovery calls. This could be from systems like Gong or Clari and effectively any calls or demonstrations or workshops that you've had with the prospect before the RFP

strategy and workshop sessions. This is really important, in the world of capture, is helping shape that RFP in a subtle way. And a big way is strategy and workshop sessions or giving updates on the state of the market and other information that helps you position the buyer to understand the world and the category that they're looking to procure their products or services in. Team interviews. So again, you might have a sales team, pre-sales team or legal compliance, they all know incredibly well what the buyer is looking for, especially if they've spoken to buyer and, or they understand the industry well. And speak to them, talk to your team, bring out internal meetings that add value and help you understand the customer and provide their knowledge into things like the strategic narrative, like the win theme for that RFP. So content is what you say and your past content, but insight is why it matters.

You can say a bunch of stuff in an RFP, and it can come out looking like gobbledygook and be of no value to the buyer, and you can get a really low mark and not tick off any evaluation criteria or compliance matrices, and you're gonna lose. Anyone can generate an RFP with AI, but insight is why it matters. And why does that matter? Again, tying back to the proposal win rate report where we interviewed and asked winning bid teams what do they rate most highly as to why they win, customer insights was the number one reason, and 88% of high win teams were doing customer insights, whereas only 67% of low win teams had a defined customer insights process. But again, of all the reasons why they win, the number one reason for high win teams was customer insights. So all that information we just spoke about, they're leveraging

that to win competitive RFPs in my same response, we're gonna jump back into our section, and we're going to ask my agent, my project agent, to look at my CRM notes, I have a couple of call transcripts in there that have been made up, and help them edit these responses based off the knowledge of that CRM. So there's my prompt. It's gonna look inside HubSpot. This is the made-up company, and it's going to go through and look at these notes without me having to effectively point it to it. It's gonna hunt and peck. And it's all fake, and it's going to use that to help respond to my fake RFP. So here you can see it's used a bunch of tool calls via the MCP. So effectively, my AI in AutoRFP.ai is speaking to HubSpot's server and grabbing all that information and then parsing that and contextualizing that for the RFP because my AI understands the RFP because it's right there in front of it. And it's going through, and it can look at all the information, and then

it's pulled out a stakeholder map. All the stakeholders and role in the decision, what they care about, and where it sourced that information. So that's really important, especially with thinking about it's actually a person behind the marking criteria. Could be procurement, could be a decision-maker and then it's talking about the actual drivers and pain points. And you can see here it's actually pulled out a lot of different information from those calls about what's important for this RFP. And it's then going to effectively take all that information, take my library content, so it's still sourced in reality of what my product and company can actually achieve, and it's going to take those win themes and must-win sections, and it's going to effectively craft that into a response. And now I'll ask it, "Cool. Can you now update section B?" Based off the context information there Again, here's two responses where it's worked in that context to that response. And you can see that I can accept that, easily make those

changes, and pretty happy with it. Those responses. That's how it would incorporate the customer insights and so on into it. I And one big thing I wanna call out is SME-led drafting, so the subject matter expert writing the response from a blank page, is a low-win habit. Ninety-four percent of high-win teams from our survey and our interviews, the proposal team writes, the SMEs review. So SMEs write for precision, whereas proposal teams write for persuasion. And we're talking back through the entire thing about customer insights, about win themes, about what makes a great response. We're talking about persuasive narrative and writing, and SMEs will write for the technical correct answer, which can be a good answer, but proposal teams write for a great answer that will actually win you that RFP. So don't fall into that trap. Make sure that when you have SMEs, they're just reviewing and approving information.

Or even better, you're sourcing that from an approved library of content that SMEs already approved, so they don't even need to approve it, but they're just reading over and approving things. But someone else is actually incorporating everything we've spoken about today into that response, and they're just approving the technicalities. One model actually that can really help speed up SME time and reduce the time as well is that AI can draft the repeatable responses, again, sourcing from approved content and then sourcing from the context of your company and the SMEs just going in and validating low-confidence bespoke responses So that's how you can use AI to help raise the floor and incorporate insight, themes, and narrative into your RFP response and really use AI to automate the mundane. Now, if you wanna get a hold of the 2026 Proposal Win Rate report that I covered throughout some of the great stats throughout today's video you can see the link in the description below. All right, thanks. I'm Rob from AutoRFP.ai.ai. Cheers.

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