The challenge
Companies have spare capacity on one side that they can’t offer quickly enough, and demand on the other that they can’t fill quickly enough. Offers and requests arrived as free text and documents in every imaginable format, comparing them was manual work, and the road from a handshake to a contract, timesheets and an invoice ran through dozens of emails and retyped data. For the marketplace to grow, the system — not an operator — had to carry most of that work.
What we built
We introduced AI as the core of the entire process. Every offer and every request goes through AI extraction that pulls structured parameters out of free text or documents — skills, scope, dates, price — and tells hard requirements apart from nice-to-haves. Matching combines semantic search over embeddings, hard filters and AI re-ranking that attaches a plain-language explanation to every match: why it fits, where the risks are and what the recommendation is. The match-quality score the client sees is kept separate from the internal, margin-aware score. Once a match is made, an automated workflow takes over — mutual confirmation, contract generation and e-signature, timesheets and invoicing — driven by background queues so nothing gets lost between steps.
Results
The platform is about to launch. Spare capacity goes from a document to an offer that is instantly comparable against demand on the market, and matches arrive with an explanation instead of a bare number. The path from match to invoice is automated end-to-end, so running the marketplace scales with deal volume, not with the number of people pushing deals along by hand.