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Nominis

Nominis argues that the established blockchain analytics firms were built for law enforcement and forensic casework, and that virtual asset service providers inherited tools shaped for a different job, with complexity, cost and integration timelines they did not need. Its answer is a platform combining wallet screening, know your transaction monitoring, forensic tools, an AsKYT assistant and intelligence as a service, with a custom risk policy builder so an institution writes its own logic.

It fuses on chain activity with open source, dark web, human and behavioral intelligence and geolocation signals, covers more than 70 blockchains and more than 2 billion labeled wallet addresses, adds more than a million addresses a day, and states screening responses under 500 milliseconds so a risky flow can be blocked before settlement. Its distinguishing asset is a curated attribution database of wallets linked to terror financing, covering state sponsored actors, proxy entities, facilitators and brokers, and it reports flagging a Hamas linked fundraising wallet six months before an OFAC designation.

The company states it has exclusively flagged $10 billion in illicit crypto. It quotes Depasify's chief executive and the founder of AML Incubator, and shows Orbital, Inca Digital, CFX Labs, Sumsub and Bits of Gold as partners. Operating as Xplorisk Ltd, Nominis was founded in June 2023 by Snir Levi in Tel Aviv, with backing from Hyperwise Ventures and Mastercard, whose accelerator program it joined.

Last VerifiedOctober 2, 2026
Compare Nominis with other vendors
Founded
2023
Headquarters
Tel Aviv, Israel
Website
www.nominis.io
Categories
crypto-and-digital-assets, aml-kyc-financial-crime
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 2 graded A or B

AI Capability
AI Centrality
CC on AI CentralityArtificial intelligence is present but peripheral: a feature layer on a product whose value stands without it.
Vendor Published

Clustering wallet addresses into entities and fusing on chain activity with open source, dark web and behavioral intelligence is work usually done with learned models, yet no technique or learned component is named. Its differentiating asset is an analyst curated terror financing attribution database, and without any models a multi source attribution service remains.

Autonomy and Oversight Model
BB on Autonomy and Oversight ModelA written commitment that the models work alongside human judgment, with real review surfaces, short of the full control structure: commonly the threshold at which the system stops or what happens after it is wrong.
Vendor Published

A custom risk policy builder lets each firm write rules for its own risk profile and jurisdiction instead of inheriting vendor thresholds. Real time blocking before settlement, however, comes with no published threshold, review requirement or notice to a wrongly blocked counterparty.

Model Risk Management and Transparency
CC on Model Risk Management and TransparencyTransparency is claimed in general terms with no mechanism a model validator could interrogate.
Vendor Published

More than 70 blockchains, more than 2 billion labeled addresses and a million added daily measure volume. False positive rate, attribution accuracy and recall against a known illicit set are unpublished.

Operational and Outcome Evidence
BB on Operational and Outcome EvidenceVendor aggregate claims with real figures, or audited scale disclosures from a publicly listed company.
Vendor Published

Manuel Roche del Fraile of Depasify and Tigran Rostomyan of AML Incubator are quoted, and a Hamas linked fundraising wallet was flagged six months before its OFAC designation. Claims of $10 billion in illicit crypto exclusively flagged and an 80 percent cut in investigation time attach to no named customer.

AI Safety and Data Stewardship
CC on AI Safety and Data StewardshipGeneral assurances that do not answer the question this axis asks, which is whether one customer’s data trains models serving its competitors. Unbounded cross client learning stated with no boundary grades here too.
Vendor Published

Public research, such as tracing how a designated network moved smuggled gold proceeds into crypto, sits beside no model card, acceptable use boundary or word on whether customer queries feed the attribution database. Commercial compliance teams and law enforcement share the platform, and a database of state sponsored actors is dual use.

Regulatory and Compliance
GLBA and Data Privacy Posture
CC on GLBA and Data Privacy PostureA standard privacy policy that covers the website rather than the service, or silence on a product that touches limited consumer data.
Vendor Published

The November 1, 2024 privacy policy names Xplorisk Ltd in Tel Aviv as controller and covers the website only. The platform's own data, which links pseudonymous addresses to people, goes unaddressed, including how a profiled person seeks correction.

Security Certifications and Trust Center
DD on Security Certifications and Trust CenterNothing published at all on security posture.
Vendor Published

Not one certification or attestation is published, nor any trust center or named security framework. Before sending screening data, a buyer has no independent review to lean on.

Regulatory Status and Licensure
CC on Regulatory Status and LicensureThe regulatory position is unstated. Most vendors in this index are technology suppliers and being unlicensed is the correct posture, so this grade records silence about the posture, not a missing license.
Vendor Published

Practical guidance engages AUSTRAC's 2026 crypto rules, New York's virtual currency regime and the FATF travel rule, while no authorization or accreditation of its own is stated. Mastercard backing and an accelerator place are commercial recognition, not regulatory.

AI Governance and Bias Disclosure
CC on AI Governance and Bias DisclosureResponsible artificial intelligence committed to in policy language with no evaluation behind it, on a product whose bias surface is modest.
Vendor Published

Terror financing attributions draw partly on open source, dark web and human intelligence and are used to block transactions, so a wrong inclusion can mean frozen funds and a report to authorities for someone outside the customer base. Governments differ on who counts as a terror financier, and no evidentiary standard for inclusion or review process is published.

AI Liability and Recourse
DD on AI Liability and RecourseNothing published on who bears the loss when the system is wrong.
Vendor Published

Terms of use effective November 1, 2024 govern the website only, and no service agreement, warranty or liability cap is published for the platform. Someone wrongly placed in the terror financing database learns only that a transfer failed, with no published notice, appeal or correction route.

Integration and Deployment
Model Supply Chain Disclosure
CC on Model Supply Chain DisclosureThe architecture is described and no provider is named.
Vendor Published

Determinations draw on several intelligence types, yet no data supplier, intelligence partner or model provider is named. Dark web material is only as reliable as whoever supplies and verifies it.

Core Systems and Integration Depth
CC on Core Systems and Integration DepthIntegration claimed through standards or connectors with no system named and nothing to verify.
Vendor Published

Responses under 500 milliseconds are fast enough to sit inline in a deposit path, and checks can run inside smart contract flows before settlement. API documentation, a developer portal and a sandbox are not published, and no exchange or custody system is named as an integration.

Deployment Model and Data Residency
CC on Deployment Model and Data ResidencyCloud only with nothing stated, which is the category norm.
Vendor Published

Hosting provider, region and residency are never named, though the company holds off chain intelligence, behavioral profiles and geolocation signals about identifiable people. Incorporated in Israel, it sells to firms under Australian, New York and European supervision.

Commercial
Commercial Transparency
CC on Commercial TransparencyNo price is published and engagement runs through a demo form, which is the norm in this index.
Vendor Published

Established providers are criticized for quoting enterprise contracts to virtual asset firms before they have enterprise revenue, yet no rate, unit or tier of Nominis's own is published. Whether the terror financing database is included or licensed separately is not stated, and entry runs through a demonstration request.

Institution and Segment Coverage
CC on Institution and Segment CoverageSegments claimed broadly, banks, fintechs, credit unions, without evidence any of them has its own maintained surface.
Vendor Published

Exchanges, custodians and banks are among the claimed buyers alongside law enforcement, yet no bank, processor or agency customer is named.

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The index publishes no overall score or ranking. See what we assess and the methodology.

Commercial

Pricing

Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.

Entry Price Pricing Basis Data Protection Terms Implementation Source
Not published. No price, unit, tier or contract term is shown; engagement starts with a demonstration request.
Quoted per customer. Wallet screening, real time transaction monitoring, forensic tools, the AsKYT assistant and a custom risk policy builder are offered across more than 70 blockchains, with no published indication of whether charges follow screened addresses, monitored transactions, chains, seats, investigations or a subscription. The entry route is a demonstration request. Not tiered on any published pricing. Nominis's privacy policy and terms of use, both dated 1 November 2024, cover the website only, and no data processing agreement, retention schedule, sub processor list, hosting location or security credential is published for the platform, which holds off chain intelligence and behavioral and geolocation signals linking addresses to people. No implementation, integration or professional services fee is published. Nominis presents fast deployment as its answer to competitors' long timelines, with an API, a dashboard that needs no engineering work and responses under 500 milliseconds for inline placement, and a policy builder the compliance team configures itself. No implementation timeline, trial, sandbox or public documentation is published. Vendor Published

Nominis publishes no rate, unit or tier as of 2 October 2026. Commercial accessibility is part of its published argument, since it criticizes established providers for quoting enterprise contracts to virtual asset service providers before they have enterprise revenue, so a buyer cannot test that claim before a sales process. Nothing indicates whether forensic tools are licensed separately from screening, or whether access to the terror financing attribution database is included.

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AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 610 vendors across banking, lending, insurance, wealth, capital markets and financial crime compliance, each graded on the same 15 capability axes from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 20, 2026
The AI FinTech Index is an editorial reference, not a regulatory body. Vendor data is verified against published sources and public regulatory filings. Figures labeled “Estimated” have not been confirmed by the vendor. See the Methodology page for evaluation standards and limitations.
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