It makes things up
Left to itself, a general AI answers from its training memory and fills gaps with confident guesses. One invented award value is enough to sink your credibility with an evaluator.
Government tender and contract data
AI-first tender research, built for people who do not take AI on faith.
Procurement Context connects Claude, ChatGPT or Copilot to published tenders, awards and supplier records. Every answer carries the record it came from, because a claim you cannot check has no place in a bid.
- Every answer cites the published notice or award it came from
- Answers draw on the connected records, not the model's memory
- Estimates are labelled as estimates, with their limits stated
The concerns
The concerns about AI are fair
Bid teams are right to be careful. A tender response is exactly the wrong place to find out what an AI got wrong. These are the four objections we hear most, stated plainly.
The same question gets different answers
Ask an unconnected AI twice and it may reach for different sources, or none. What it finds depends on the chat, not on the record.
There is no source to check
A chat answer without a citation cannot be verified or audited, and it cannot be carried into a document an evaluator will scrutinise.
Nobody knows what it looked at
Without a fixed data connection there is no answer to the governance question: what did the AI actually consult before it answered?
The design answer
Built to deal with each one
- Grounding: answers draw on the connected registers of tenders, awards and suppliers, not the model's memory of the internet
- Citations: every response returns the underlying notice or award, so a claim traces to a public source an evaluator can check
- Consistency: one fixed connection every time, not whatever your AI happens to reach for in that chat
- Honest numbers: win rates and revenue figures are estimates from public records, presented as estimates. A supplier's public awards are a floor, not a full picture, and we say so
Where the line sits
What we use AI for, and what we do not
AI does the retrieval: finding, joining and summarising thousands of published records in seconds, in plain English. It does not make your decisions. The go or no go call, the pricing call and the bid itself stay with your team, argued from the record instead of from memory.
The connection
How it connects
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01
It plugs into the AI you already have
Procurement Context runs as an MCP server. That is the standard Claude, ChatGPT, Copilot and most enterprise AI tools already use to reach external data. Connecting is a configuration step, not an integration project.
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02
Your team asks in plain English
"Which agencies bought facilities management in Queensland last year, and who won?" No query language, no CSV export, no new interface for anyone to learn.
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03
The answer cites the record
Responses come back with the underlying notice or award attached, so a claim you carry into a bid traces to a public source an evaluator can check.
Coverage
If it's public, we cover it
Coverage is portal-agnostic. We have a system for standing up a new portal quickly, so any public procurement source is effectively already covered. Tell us where you tender and we will confirm it.
Portals our customers ask for most
North America
- SAM.gov (US federal)
- Cal eProcure
- NYS Contract Reporter
- CanadaBuys
- BC Bid
United Kingdom
- Find a Tender
- Contracts Finder
- Public Contracts Scotland
- Sell2Wales
Europe
- TED (pan-EU)
- e-Vergabe (Germany)
- BOAMP and PLACE (France)
- TenderNed (Netherlands)
Australia
- AusTender (federal)
- buy.nsw
- Buying for Victoria
- QTenders
- Tenders WA
- SA Tenders and Contracts
- Tasmanian Government Tenders
- Tenders ACT
- Quotations and Tenders Online (NT)
New Zealand
- GETS
Asia Pacific
- GeBIZ (Singapore)
- GeM (India)
Hover or tap a market to match it to its portals.
Not an exhaustive list. Commercial aggregators such as VendorPanel and TenderLink are covered too, alongside the public sources above.
We have all started using AI to write our tenders. But good data to use as context is still the hard part, and it is the part that decides whether the bid was worth writing at all.
Tell us what you would want it to answer.
Four questions, so the conversation is useful. We come back to you directly.
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Book a timeQuestions
- Do we have to use MCP?
- No. MCP is how it connects to Claude, ChatGPT, Copilot and most enterprise AI tools, and for most teams that is the fastest route because the client is already on their desks. There is a direct API if you are building something of your own, and we can run scheduled briefs into email or Slack if you would rather the answers came to you.
- Which portals do you cover?
- If a portal is public and publishing, we cover it. We have a system for standing up a new source quickly, so coverage is not limited to a fixed list. The examples above are the ones customers ask for most. Tell us where you tender and we will confirm what is already running.
- Where does the data come from?
- Public tender portals and award registers: notices, awarded contracts, contract values and supplier records, as published by the buying organisations themselves. Every response cites the underlying record.
- How accurate are the win rates and revenue figures?
- They are estimates derived from public award records, and we present them as estimates. A supplier's public awards are a floor, not a full picture: private work and subcontracting never reach a register. It is enough to tell you who the serious incumbents are and how often they win.
- How is this different from a tender alert service?
- Alert services tell you what is open. The harder question is what has already been awarded, to whom, and for how much. That is what tells you whether a bid is worth writing. Procurement Context covers both, and it answers questions rather than sending you a list.
Tell us what you would want it to answer.
Four questions, so the conversation is useful. We come back to you directly.