Tender & Opportunity Intelligence
An AI agent reads each incoming tender, scores it against what the company can actually deliver and returns a go/no-go recommendation with the reasoning written out.
The problem
Inbound opportunities arrived every week - RFPs, partnership enquiries, referrals, tender notices. Someone senior read the document and decided from experience. There was no shared framework, no written reasoning and no way to learn from past decisions.
So the team sometimes spent weeks on bids that were never a good fit, and the warning signs - unrealistic timelines, mismatched capabilities, low-margin structures - were spotted late or not at all.
What we built
- A scoring framework - agreed with the leadership team. Every opportunity is assessed on strategic fit, delivery feasibility, commercial viability, competitive position and risk.
- An AI evaluation agent - reads the document, cross-references the company’s knowledge base and applies the framework. Out comes a score per dimension, a go/no-go recommendation, flagged risks and a plain-language summary.
- A lessons-learned loop - the outcome of every pursued opportunity feeds back in.
- A structured archive - every assessment follows the same template, so past decisions can be read back.
Stack: Claude · Custom scoring framework · Document parsing · Knowledge base integration
The result
Senior people spend their time on the bids worth winning, and every decision leaves a written rationale that the next person can read.