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Service

Tangos runs your investigations.

Submit cases, receive examiner-ready reports with source-traced evidence. Pay per case. No infrastructure required.

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Platform

Your team operates autonomous investigators.

Full visibility into every step, every evidence source, every reasoning chain. Cloud, private cloud, or on-premise. Case-based pricing.

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Where Judgment Breaks, And How Tangos Reconnects It

Alert overload

Adversarial typologies scale faster than analyst capacity.

Documentation failure

Inadequate investigations produce indefensible files.

Evidence gaps

Investigations get rushed or under-resourced.

Tangos closes the seams.

A continuous reasoning fabric links detection, investigation, and decision.

Careers

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Careers

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Careers

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Context-Trained Systems That Continuously Improve

Off-the-shelf does not reach the bar. Context-trained systems do.

A general-purpose system will get you close. Close is insufficient. Every organization operates under a distinct regulatory framework, risk profile, and output standard. A system not trained to that context will plateau below the threshold that matters.

Tangos deploys, then fine-tunes — against your cases, your regulatory context, your requirements. A continuous loop, not a one-time pass:

Observe → Test → Compare → Refine → Repeat.

Each cycle tightens precision within your context. The loop does not close — it compounds. This is how near-perfect accuracy becomes an engineering outcome, not a marketing claim.

Context-Trained Systems That Continuously Improve

Off-the-shelf does not reach the bar. Context-trained systems do.

A general-purpose system will get you close. Close is insufficient. Every organization operates under a distinct regulatory framework, risk profile, and output standard. A system not trained to that context will plateau below the threshold that matters.

Tangos deploys, then fine-tunes — against your cases, your regulatory context, your requirements. A continuous loop, not a one-time pass:

Observe → Test → Compare → Refine → Repeat.

Each cycle tightens precision within your context. The loop does not close — it compounds. This is how near-perfect accuracy becomes an engineering outcome, not a marketing claim.

Sanctions adjudication, transaction monitoring investigation, SAR case management, cross-border payment risk, and AML compliance. Investigations closed end to end. Each program is pre-configured for a specific segment with the regulatory frameworks, data sources, and evidentiary standards that segment requires. Examiner-ready output with source-traced evidence and full audit trails.

Sanctions adjudication, transaction monitoring investigation, SAR case management, cross-border payment risk, and AML compliance. Investigations closed end to end. Each program is pre-configured for a specific segment with the regulatory frameworks, data sources, and evidentiary standards that segment requires. Examiner-ready output with source-traced evidence and full audit trails.

Sanctions adjudication, transaction monitoring investigation, SAR case management, cross-border payment risk, and AML compliance. Investigations closed end to end. Each program is pre-configured for a specific segment with the regulatory frameworks, data sources, and evidentiary standards that segment requires. Examiner-ready output with source-traced evidence and full audit trails.

Almost Right Is Not Good Enough

In risk and financial crime investigation, a wrong output is not an iteration. It is a regulatory, financial, and reputational consequence. Institutions in this space act on every output they receive. That demands a standard most technology was not built to meet.

Generalist LLMs reach 70–80% accuracy. Enforcement-grade environments cannot tolerate that gap. Reaching near-perfect accuracy — consistently, verifiably, defensibly — is a different engineering problem. It requires judgment encoded into the system from the ground up, by people who know what right looks like, what breaks under real pressure, and what a regulator actually scrutinizes.

Tangos was built domain-first. People who have investigated sanctions targets, operated inside tier-one institutions under real compliance constraints, and built enforcement programs at scale — then built the platform to do that work at the scale the problem demands.

The engineering follows the judgment — not the other way around.

AML Alert Investigation

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AML Alert Investigation

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AML Alert Investigation

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AML Alert Investigation

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Context-Trained Systems

Five layers. Each one exists because the problem demanded it.

Tangos tertPrograms

The operational layer. Configurable investigatirteron programs, fine-tuned to your risk context.

Build Hypotheertertsis

Multiple htertreypotheses are formed where the typology demands it. No assumptions carried forward without evidence.

Test Evidreterteence

The engine queries across dertertata sourctertereres, jurisdictions, and languages.

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The Investigation Arc

Ingest Alert

Tangos receives the case via API, email, batch, or UI. No process change. Integrationless by design.

Build Hypothesis

Multiple hypotheses are formed where the typology demands it. No assumptions carried forward without evidence.

Test Evidence

The engine queries across data sources, jurisdictions, and languages — then validates every conclusion against counter-evidence. This is the cycle that reaches near-perfect accuracy.

Examiner-Ready Report

A complete case file — defensible conclusion, source-traced evidence, immutable audit trail. Ready for examiner review, regulatory submission, or internal sign-off.

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Prograerterm Title

Sanctions adjudication, transaction monitoring investigation, SAR case management, cross-border payment risk, and AML compliance. Investigations closed end to end. Each program is pre-configured for a specific segment with the regulatory frameworks, data sources, and evidentiary standards that segment requires. Examiner-ready output with source-traced evidence and full audit trails.

Proerwgram Title

Program description goes here.

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