Project context
Tender Drafting from Internal Knowledge
AI tender workflow that turns an RFP into a structured first draft by matching requirements to internal case studies, CVs, and reusable proposal knowledge.
Client identity kept confidential
Evidence
Measured in a focused validation across five historical tenders. Drafts were assessed as starting points, not submission-ready proposals.
The challenge
The solution
Technology stack
The result
Bid managers rated the generated drafts as a usable starting point rather than a novelty output: 3.8/5 on average versus 4.5/5 for the original manually written winning submissions. First drafts arrived in around 12 minutes instead of 2 to 3 days, and the retrieval layer selected the right supporting material in 4 out of 5 tenders without manual correction.
That changes the economics of tender work. Less time disappears into reconstruction, and more time stays available for sharpening positioning, proof, and win strategy.
Next step
Want to explore where this could land first in your operation?
Start with one concrete process. In the AI Opportunity Scan we assess where AI adds value and what the best first route looks like.
