Six steps from solicitation upload to a protest-defensible award recommendation. AI accelerates the preparation; your committee stays in control of the decision.
The committee chair uploads an RFP or RFQ to private storage. PropEval AI reads the document and extracts a proposed evaluation framework, including criteria, weights, rating scales, and mandatory requirements.
The chair reviews the AI-extracted framework, edits criteria or weights to match agency-specific guidance, and locks it. The locked framework becomes the basis for every proposal analysis and evaluator score.
Vendors' proposals are uploaded and analyzed against the locked framework. PropEval AI produces a scored criteria matrix with evidence citations and a compliance gap report for each proposal.
Committee members score in private workspaces with AI recommendations available as a reference. Peer scores stay hidden until the consensus phase, preserving evaluator independence.
The chair reconciles evaluator scores into a consensus result. Divergence scoring surfaces where evaluators disagree so discussion focuses where it matters.
PropEval AI generates a comparative ranking and award recommendation. The chair exports a protest-defensible report with the full audit trail of every scoring event, override, and comment.
Source selection has always depended on careful human judgment. AI doesn't replace that judgment — it gives every evaluator a sharper, faster, more consistent starting point.
AI applies your locked framework the same way to every proposal, so scores reflect the submission — not which evaluator read it first or how tired they were on page 40.
Every AI score comes with a citation to the exact passage in the proposal that supports it. Evaluators start from evidence, then adjust with their own expertise.
When evaluators disagree, PropEval AI quantifies the gap so the chair spends consensus time on the criteria that matter — not re-litigating the ones everyone already agrees on.
The result: evaluators spend their time on judgment, not on page-counting. Committees reach consensus faster, with an audit trail that shows exactly where AI informed the decision and where a human overrode it.
Start with a single committee, or arrange a free guided pilot for one live evaluation.