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Inventive AI
RFP.ai helps teams answer RFPs, DDQs, and security questionnaires with AI drafts grounded in approved sources, citations, confidence cues, and reviewer control.

Website, pricing, platforms and company facts side by side.
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| Website | rfp.ai | codegres.org |
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| Company | Startup from the Netherlands · 1 - 9 employees · 2026 | — |
| Listed in |
In their own words, as submitted to SaaSHub.


RFP.ai is an AI-powered response platform for teams that answer RFPs, RFIs, DDQs, vendor questionnaires, and security assessments. Instead of starting from a blank page, teams can upload approved documents, past proposals, policies, product sheets, security answers, and other trusted source...
No description of Codegres.org yet.
What each product offers, as listed by its team.


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As answered by people managing RFP.ai and Codegres.org.
RFP.ai's answer
RFP.ai does not publicly disclose customer names.
RFP.ai's answer
RFP.ai focuses on source-backed answers rather than generic AI writing.
The platform drafts responses from approved company documents, past proposals, policies, security material, and other trusted sources. Each answer can include citations, confidence cues, and reviewer control, so teams can see where an answer came from before using it.
That makes it useful for high-stakes RFPs, DDQs, RFIs, and security questionnaires where accuracy, evidence, and review matter.
RFP.ai's answer
Choose RFP.ai if you want a focused, lightweight RFP response platform with source citations, confidence cues, and human review built into the workflow.
Many proposal tools focus on content libraries or broad proposal management. RFP.ai is built around the practical problem most teams face: the answer already exists somewhere, but it is buried in old proposals, shared drives, policies, spreadsheets, or internal documents.
RFP.ai helps teams find, draft, review, and export responses faster without relying on unsupported AI-generated claims.
RFP.ai's answer
RFP.ai is built for proposal teams, presales teams, sales engineers, security teams, compliance teams, and B2B SaaS companies that regularly answer RFPs, RFIs, DDQs, vendor questionnaires, and security assessments.
It is especially useful for teams that already have approved content, but lose time searching across old proposals, document folders, spreadsheets, and internal knowledge bases.
RFP.ai's answer
RFP.ai was built to solve a common proposal workflow problem: teams were rewriting the same answers over and over, even though the right information already existed somewhere inside the company.
The product was designed around a simple idea: AI should not invent proposal answers. It should retrieve approved knowledge, draft a usable response, show the source, flag uncertainty, and let the team review before submission.
That is why RFP.ai combines AI drafting with citations, confidence cues, human review, and export workflows.
RFP.ai's answer
RFP.ai uses AI language models, retrieval-augmented generation, document parsing, semantic search, source citation workflows, browser automation, and MCP-based integrations.
The product is designed to work with company knowledge sources such as past proposals, policies, security documents, product sheets, and approved answer libraries.
Share your experience with using RFP.ai and Codegres.org. For example, how are they different and which one is better?
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