Fused intelligence you can defend.
Dark-web context, on-chain provenance, and identity — correlated into one court-defensible graph. With published error rates.
Measured 2026-09-09. Every one of these is downloadable, free, under CC BY 4.0 — click any figure.
Here is a finding, rather than a claim.
Of 1,979 cryptocurrency addresses on the OFAC SDN list, across 19 chains — Tron carries more than Ethereum.
404 designated addresses on Tron against 233 on Ethereum: 73% more (171 additional), on a chain much screening tooling still treats as a secondary integration.
Which decides your coverage
Screen Bitcoin and Ethereum only, and you cover 1,293 of 1,979. You miss 686 (34.7%).
Treasury publishes this list. Download
SDN.XML, count the digital-currency features by currency code,
and you should get these numbers —
the working is here, and the
full address list is in the free datasets.
To investigate money that moved through the dark web, you need three products.
One traces the chain. One has the darknet corpus. One does infrastructure and identity.
Together they cost more than €300,000 a year. None of them fuses with the others. None fuses with your own data.
So an analyst on your team becomes the integration layer — and that is the most expensive way there is to get an answer.
We are the correlation.
One graph. One query. Four hops that would otherwise be four products and an analyst copying identifiers between them:
- 1Marketplace listingHidden-service crawl across Tor, I2P and Freenet
- 2The wallet that paidObserved on our own full node — block height and time, not a vendor’s API
- 3The off-ramp that cashed outCross-chain tracing and deposit clustering
- 4The entity behind itCorporate registries, beneficial ownership, sanctions screening
Each hop names the evidence behind it, because the join is only worth as much as the weakest link in it.
No tool switching. No re-keying identifiers. The correlation is already done.
Four things nobody else has together
We run the nodes
First-party ground truth from twelve-plus blockchain full nodes we operate ourselves. Block heights in your audit record, not a resold vendor API.
We publish our error rates
Measured against a closed-loop chain where we hold the answer key, plus honeytoken assets that produce confirmed evidence. Ask any other vendor for theirs.
Glass box, always
Every score ships per-feature contributions. Every alert cites the FATF or FinCEN rule. Every brief cites the rows it came from.
Civil liberties, audited
We found inferred ethnicity in our own product and published what we did: 4,059,250 rows deleted, 13,801 already-served scores withdrawn. The producers sit behind a gate that fails closed.
Don't take our word for any of it
We publish six datasets, free and unrestricted, built from public-domain government records and from a Bitcoin archival node we operate ourselves. Every summary figure in them is a live formula pointing back at the rows behind it, so you can click any number and trace it.
They include the places our own work is weakest. One workbook documents a defect in our own CoinJoin detector and publishes the filtered subset we would actually stand behind, rather than the flattering headline number.
Bring us a case you have already worked.
Not a demo on our data — a real matter where you already know the answer. It is a better test than anything we could show you.
Built for asset-recovery and crypto law firms, fusion centers and financial-crime units, crypto investigators, VASP compliance teams, and investigative newsrooms — the people priced out of the incumbent stack. Whether that is you.