Revive AI
Revive provides a controlled RFP-to-bid workflow platform that helps proposal and engineering teams turn complex, 300+ page RFQ packages into verified, reviewable bids. The platform extracts requirements across specifications, drawings, and datasheets while preserving source context, and separates verified project scope from assumptions requiring engineering review. Ask AI assists teams in refining proposals by comparing responses against customer requirements with supporting evidence.
- Artificial Intelligence
- Software Only
- AI Agents
Funding
Founders
Founder details are not available yet.
Product
Problem
Complex RFQs can take up to a month to turn into a bid, with requirements hidden across specifications, drawings, datasheets, amendments, equipment lists, and supplier quotes. Missing a single cross-document dependency can lose the bid or result in an expensive scope gap after award. Manual review is too slow, while generic AI tools produce fast answers that cannot be trusted for accuracy.
Solution
Revive gives proposal and engineering teams a controlled workflow from first-pass read through final technical proposal, turning 300+ page RFQ packages into verified, reviewable bids. The platform reads the entire package, extracting requirements across specifications, drawings, appendices, and revisions while preserving source context. It separates verified project scope from general guidance, missing quantities, and claims requiring engineering review. Ask AI helps teams refine proposals by comparing responses with customer requirements, examining costs and assumptions, and identifying questions that need clarification—all supported by project evidence and statistical analysis.
Target Audience
Primary users are proposal and engineering teams at companies that respond to complex, specification-heavy RFQs in industrial sectors such as engineering, construction, and equipment manufacturing.
Features
- End-to-end RFP-to-bids workflow rather than a chat-window interface
- Cross-document requirement extraction spanning specifications, P&IDs, datasheets, equipment lists, and supplier quotes
- Source-context preservation so every extracted requirement traces back to its origin
- Fact-versus-assumption classification that flags missing quantities and items needing engineering review
- Structured proposal assembly combining approved product content with project-specific facts
- Ask AI assistant for comparing responses against customer requirements, reviewing scope, challenging costing assumptions, and exploring alternatives with supporting evidence