AI Proposal and RFP Response Automation, Built on Your Own Work

AI can read the solicitation, list every requirement, find gaps and draft sections from your past work, which removes most of the reading and first-draft time. A person should still review and approve what is submitted, and the systems we build are designed around that review.

Past proposals, project write-ups and your company profile are split into chunks, embedded and stored in a vector database such as Pinecone. For each new request, the system retrieves the few most relevant examples and drafts from those, a technique called retrieval-augmented generation (RAG).

That is the main risk, so the prompt allows only past work that was retrieved, tells the model to say when nothing is relevant, and reviewers check every draft. The evaluation set we build for each project includes cases that check for invented claims.

Off-the-shelf proposal tools work well for standard questionnaires and answer libraries. A custom system makes sense when your solicitations are long or scanned, when you need checks specific to your business, or when it must run inside your own systems and cloud.

A pilot on your own RFPs usually takes 2–4 weeks and starts at $5,000. A production system with integrations, evaluations and monitoring takes longer, depending on scope.