Who is buying, and what is next
What an agency has bought, from whom, at what value, and on what cycle. Contracts coming up for renewal are the pipeline nobody has published yet.
No new dashboard. ChatGPT connects to the source data and answers there.
Competitive intelligence in public procurement has an unusual property: it is almost entirely public and almost entirely unread. Every award is published. Nobody has time to read them in aggregate, so teams rely on what they observed directly, which means they know about the bids they were in and very little about the ones they were not.
Connecting the award records to ChatGPT makes the aggregate view cheap enough to bother with. Ask where a named competitor has won over a period, which buyers keep selecting them, and whether their work is concentrated in one category or spread across several. The answers come from the published notices, which is a more reliable source than the impression left by the last three tenders you lost.
One caution worth stating plainly: the record shows outcomes, not reasons. It can tell you a supplier has won a buyer's work five times. It cannot tell you whether that is price, an incumbent advantage or a genuine capability gap. What it does is narrow the question down to something a person can actually investigate.
What an agency has bought, from whom, at what value, and on what cycle. Contracts coming up for renewal are the pipeline nobody has published yet.
The suppliers who keep winning in a category, with their award history and estimated win rate. Know the incumbent before you commit a team to the response.
Awarded contract records with values and dates. Price against evidence of what this buyer has paid before, not against a guess.
Open opportunities across every covered portal, filtered by the criteria your team actually qualifies on.
Four questions, so the conversation is useful. We come back to you directly.
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