Paste any wallet address: Anoxir collects its full transaction history across chains, scores risk with a multi-model ML ensemble, screens sanctions and scam registries, traces tainted funds hop by hop — and generates court-ready forensic reports in seconds.
Platform Capabilities
Anoxir collects the full on-chain history of any wallet, scores its risk with a machine-learning ensemble, screens sanctions and threat-intel registries, then packages everything into forensic-grade reports.
Follow tainted funds hop by hop across the network — the taint engine tracks value through DEX swaps, cross-asset transformations and mixer detours, with evidence stamped on every hop.
Generate professional-grade PDF reports in one click. Structured around Mandiant/CrowdStrike-style frameworks: facts → patterns → interpretation → conclusions.
Every address is checked against OFAC SDN, curated blacklists, community scam registries and whitelists — a confirmed hard fact always overrides any model output.
Interactive graph visualization of entity relationships and fund flows. Automatically identifies clusters, bridges and high-risk propagation paths — and recognizes known fraud topologies: pig butchering hubs, address-poisoning vanity addresses, honeypots, drainer kits, rug pulls, dust attacks and cash-out paths.
Random Forest, Gradient Boosting, GNN and GCN models score every wallet in ensemble on each analysis. Every signal is weighted, explainable, and capped by hard facts.
Workflow
Paste any wallet address — EVM chains, Solana or Bitcoin. Anoxir routes it through 9 intelligence sources and collects its full on-chain history in parallel.
ML models vote in ensemble — behavioral, graph, temporal — producing a composite, explainable risk score for every address on the path.
Download a structured forensic PDF or raw JSON for integration into your existing compliance toolchain.
One platform, three levels
Anoxir adapts to who's asking. Basic users get an instant answer on a given address. Analysts go deep and build the full picture of a suspect operation — or formally clear an address of any red flag. And on top sits a supervised AI layer that turns raw results into plain language.
Paste a wallet address and get an immediate verdict against the 9 intelligence sources — sanctions lists, scam reports, phishing registries, curated whitelists. In seconds you know whether an address appears anywhere in the known-threat landscape, before sending funds or interacting with a counterparty.
The complete investigation: full transaction history, fund-flow graph, hop-by-hop taint tracing, and the ML ensemble scoring every address on the path. Use it to document a scam end to end — identity of the clusters, flow of the funds, destination venues — or to formally verify the opposite: that an address carries no red flag, with the evidence trail to prove it.
A supervised AI layer reads the generated data — graph, scores, signals — and restates it as comprehensible text: what happened, why the score, what matters next. It assists investigations by pointing to the hop that needs attention, suggesting leads to clear a doubt, and writing the narrative sections of the exported report. It never invents facts: every sentence traces back to data.
Community evidence
Anoxir doubles as a reporting channel. Victims file structured testimonies against a scam address (type of scam, prejudice amount, evidence screenshots/documents) — or, on the contrary, file a formal defense for a wrongly flagged address. Reports rated credible by the review workflow feed the threat-intel layer used by every future analysis.
How the scoring works
Most risk tools give you a number you have to trust blindly. Anoxir Technologies shows its reasoning. Every assessment is built in three layers, and every signal that contributes to the final score is listed with its own confidence — so an analyst can defend the conclusion, not just quote it.
First we check hard, verifiable facts — regulatory lists, known-good registries and community intelligence. A confirmed fact is what drives a strong verdict, never a model guess alone.
An ensemble of ML models votes — decision forests, gradient boosting, graph neural networks, temporal models. Each contributes a weighted, explainable signal rather than a single opaque output.
Finally we measure exposure to the surrounding network — clusters, bridges and propagation paths — to understand risk by association, not just the entity in isolation.
A model on its own can flag for review, but it can never produce a maximum-risk verdict by itself. A severe conclusion always requires a hard, verifiable fact behind it.
In-app panels describe each algorithm in plain language, and exports include the per-signal breakdown — so the analysis is understandable without a data-science background.
Product tour
A look at the analyst workspace, the relationship graph, and the reports you can export.
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Graph Intelligence
Anoxir Technologies' graph engine maps relationships and propagation paths across your entire dataset — automatically clustering entities, surfacing hidden bridges, and quantifying risk exposure by neighborhood.
Pricing
Start with a single one-time analysis, or scale with a subscription when your caseload grows. Prices are in euros and take effect at purchase on anoxir.io.
🚀 Launch pricing — these rates are promotional and will increase at public launch. Early testers run analyses for free on anoxir.io while the offer lasts.
One-time purchase.
Billed monthly. Cancel anytime.
Billed monthly or annually.
Billed monthly or annually.
All prices are in euros and exclude applicable taxes. Subscriptions renew automatically and can be cancelled at any time from your account. See our Refund & Cancellation Policy.
The full platform is live: paste a wallet address, get the fund-flow graph, the risk score and the forensic report. No waiting list, no sales call required — analyses are free for the first testers while launch pricing is in effect.