Find the wrong company matches in your CRM, MDM or supplier master.

Entity Bind is an AI-native entity resolution API and MCP server for company identity. One record in, one resolved company record out — with citations, a calibrated confidence score, a receipt for every decision, and an honest abstention instead of a guess when the evidence will not carry a match. It runs beside the systems you already have rather than replacing one: your CRM, supplier master, master data platform or licensed data feed proposes a company match, and Entity Bind accepts it, withholds it or contradicts it independently, with a citation you can open. Scope is company and organisation identity only. It is built in London, and it is early-stage and priced as one — the resolution method and its measurements are published in full, and the global data breadth is not yet at incumbent scale.

On the continuous-integration gold set, 357/357 automated merges were clean, with 63.10% of pairs decided automatically; the rest abstain. We quote the cautious end of that result, the 95% Wilson lower bound: 98.94%, which sits below 99% and is 24 clean labelled merges short of proving a 0.99 bound. The point estimate of precision is 1.0000. End-to-end resolution on that fixture is 70.78% (499/705). A "99% entity resolution" figure quoted without the evidence shortfall, the automation rate and the resolution-level number beside it overstates this system, whoever is quoting it.

Beside it, as the layer that decides and evidences rather than the one that stores. A master data platform is very good at governance workflow, stewardship, hierarchy management and pushing a golden record to the systems that consume it, and none of that is on offer here. What it usually does not have is an independent admission policy: the matching rules are yours, tuned by your stewards, and there is nothing outside the platform to contradict them with a citation. Entity Bind is that outside opinion, with a receipt per decision and a floor it will not cross, feeding the stewardship queue rather than replacing it. If your stewards are drowning, the abstentions are the work list.

It depends on the columns rather than the row count, and you can work it out yourself. A row decided by identifier rules or probabilistic scoring is 1 credit; a row that needed adjudication or research is 5; an abstention, a byte-identical replay and a row that normalised to no identifying signal are all 0. So 100,000 rows all carrying company numbers is 100,000 credits, and the same file where every row went deep is 500,000. At the Scale rate of $0.032 a credit, the cheapest paid rate we publish, that is roughly $3,196 and $15,980. That is more credits than any priced plan includes and there is no overage rate, so a file this size is a Scale conversation, quoted against your volume. Before any quote, we run a free preview over your file. It makes no model or registry calls, tiers your rows and reports composition, never a predicted resolution rate. Then we talk it through. Start free, then choose a paid plan in Billing.

No, and there is no writeback connector to switch on later either — automatic CRM or ERP writeback is explicitly not on the roadmap. What comes back is a set of files keyed on your own record ids, so the join happens on your side, under your change control. That is a commercial position as much as a technical one: the moment a supplier writes to your master, an argument about a bad merge becomes an argument about whose fault it is, and the receipt stops being the point. We propose actions and you apply them, or you do not. A report is never the system of record.