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Ledger

Agentic AI for bid + tender intelligence

James Reed|May 8, 2026|8 min read

Key Takeaways

  • -Tender platforms aggregate notices; they do not tell you which to bid on. Capability-match scoring against the operator's win history is what turns the feed from noise into shortlist.
  • -Bid drafting is the natural extension. Once the system has a confident match, it can produce a structured first-pass response aligned with the awarding authority's published evaluation criteria.
  • -Evidence libraries matter more than templates. WYRM Ledger pulls from the operator's prior winning bids and accreditations, surfacing where claims are supported and where new evidence is required.
  • -Available across Find a Tender, Contracts Finder, SAM.gov, and BDUK. Capability-match scoring on Pro; full Tender Writer drafting on Enterprise.

Anyone who has run a bid function knows the bottleneck is not finding tenders. It is deciding which ones to bid on, and then producing a credible response inside the published deadline. The aggregation platforms — Tussell, Tracker, Bidstats — solve the first problem, sort of. They surface every notice that matches a broad sector filter. What they do not do is tell the operator which notices are worth pursuing and which are pre-wired for an incumbent. That decision is still made by hand, usually badly, usually under time pressure.

WYRM Ledger approaches the same data stream with a different goal. Ingest the same Find a Tender, Contracts Finder, SAM.gov and BDUK feeds, but score every notice against the operator's capability profile and historical win pattern, then return a ranked shortlist with a fit score per opportunity. The score is not opaque — it is composed of named factors the operator can inspect: sector match, geographic fit, contract value relative to past wins, evaluation criteria coverage, incumbent presence, and time-to-deadline given current bid load.

The fit score does what a human BD reviewer does mentally in the first five seconds of looking at a notice, except it does it for every notice every day. The human time is then spent on the small set that scored well, not on the firehose. That alone is a meaningful efficiency, because the firehose is what burns the BD function out — not the bids, the triage.

Once a notice passes the threshold, the second agent kicks in. The Tender Writer drafts a structured first-pass response. Not a finished bid — a draft. It pulls from the operator's evidence library and prior winning bids, structured against the awarding authority's published evaluation criteria. Where a claim is supported by evidence in the library, the draft cites it. Where it is not, the draft flags it as requiring new evidence. The operator's job is to redline, supplement, and finalise — not to start from a blank page.

This pattern only works because the underlying substrate is agentic. The tender-match agent and the bid-drafting agent are separate specialists. The match agent does not draft. The drafting agent does not score. They share a context — the notice, the operator profile, the evidence library — and produce structured outputs that compose into a workflow rather than a single LLM dump.

A practical example. A mid-market civils contractor with a strong record on Highways England framework lots receives a Find a Tender notice for a county council bridge-strengthening programme. The match agent scores it 84/100 — strong sector match, geographic fit good, contract value typical, evaluation criteria 78% covered by the operator's evidence library, no obvious incumbent. The Tender Writer drafts the technical response section using the operator's prior bridge-strengthening case studies, flags two evaluation criteria where the evidence library is thin, and prepares a structured pricing schedule template. The operator's BD lead opens the draft, redlines two paragraphs, briefs the engineer to produce the missing two pieces of evidence, and the bid is competitive on day two of a four-week deadline.

Public-sector buyers are starting to notice the difference, by the way. A response that demonstrably uses the awarding authority's published evaluation criteria as section headings — rather than a generic capability statement — scores better in the moderated evaluation. That is not a Ledger trick; it is just disciplined bidding. What Ledger does is make that discipline the default rather than the exception.

The pricing reflects the depth of the lift. Pro at £19/month includes the tender feed, capability-match scoring, and a basic Bid Assist surface for redlining. Enterprise at £49/month adds the full Tender Writer agent, deeper integration with the evidence library, and the surrounding Ledger capabilities — CBAM accounting, HMRC MTD/VAT, customs reconciliation, and the seven-year audit-trail archive. Ledger is one of WYRM's focused add-on modules; it sits alongside the flagship engineering products, WYRM MEP and WYRM Data (bundled as WYRM Engineering at £250/seat). Operators bidding on contracts that also need supplier evidence (Procure), cyber attestation (Cyber), or contract redlining of the framework T&Cs (Legal) can run those modules side by side on the same substrate.