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deepidv · AML Transaction Monitoring

Every transaction.
Scored in real time.

deepidv scores every transaction in under 150ms with behavioral anchoring, adaptive ML, and network analysis — catching structuring, layering, and laundering patterns that rule-based systems miss entirely.

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DocumentationDeveloper docs

deepidv scores every transaction, explains which rule fired, and raises the alert — before the money settles.

aml · live ledger<150ms

Acme Pay

TX-90431

$3,1008

Nomad LLC

TX-90423

$9,85064

Wallet 0x9f

TX-90418

$48,90091

Score every transaction

Behavioral anchoring and adaptive ML return a composite risk score in under 150ms — inline decisioning to block, hold, or pass with no batch delay.

aml · typologyRisk 91

AML-LAY-12Layering

AML-STR-04Structuring

AML-RTP-09Round-trip

Catch laundering patterns

Network and relationship analysis maps connected entities to surface structuring, layering, and round-trip schemes that rule-based systems miss.

aml · case docketReal time

Open · C-2039

Investigating · C-2041

SAR filed · C-2036

Raise & resolve alerts

Suspicious activity opens a case with an auto-drafted SAR/STR narrative — formatted for FinCEN, FCA, AUSTRAC, and 50+ regulators.

By the Numbers

Built to catch what others miss

Real-time scoring, fewer false positives, and broad regulatory coverage — across every financial flow you run.

<150ms
Scoring Latency: 99.2%
Detection Rate: 85%
False Positive Reduction: 50+
Regulators Covered

Real-Time Scoring

Every transaction, scored before it settles

Each transaction is evaluated by an ensemble of models running in parallel — behavioral deviation, network context, rule matching, and anomaly detection — and returns a composite risk score in under 150 milliseconds for inline block, hold, or pass.

Scoring engine

Sub-150ms Scoring

Before settlement, every time

Inline Decisioning

Block, hold, or pass

Behavioral Anchoring

Dynamic per-customer baselines

Adaptive ML Models

Self-tuning, analyst-trained

aml · live ledgerscoring

IDTypologyAmountRisk

TX-90431

82ms

Payroll → Staff ••08

—

$3,1008

TX-90423

121ms

Nomad LLC → Off-shore

AML-STR-04

$9,85064

TX-90418

97ms

Wallet 0x9f → 0x2c

AML-LAY-12

$48,90091

TX-90412

74ms

Acme Pay → IBAN ••71

—

$1,24012

4 scored · 1 flagged · 1 review<150ms avg

Pattern Detection

Surface the laundering schemes

Network and relationship analysis maps transactions to connected entities — exposing structuring, layering, and round-trip patterns, and surfacing fraud rings and coordinated laundering that single-transaction rules can never see.

What we catch

Structuring & Smurfing

Sub-threshold splitting

Layering

Wallet clusters & chain-hopping

Round-Trip Movement

Rapid in/out flows

Network Analysis

Connected-entity mapping

aml · pattern analysisalert · TX-90418

Suspicious activity

$48,900 · Wallet 0x9f → 0x2c · cross-border

91risk

0x9f

origin

0x2c

wallet A

0xf4

wallet B

LLC

shell co.

4-hop layering route

Typology chain

AML-LAY-12Layering detected

AML-STR-04Structuring signal

AML-NET-07Network cluster match

Cases & Reporting

From alert to filed report

Every flagged transaction opens a case with a full audit trail. The system auto-generates SAR/STR narratives with supporting evidence, pre-formatted for submission to FinCEN, FCA, AUSTRAC, and 50+ regulators — so your team investigates real threats, not noise.

Investigation workflow

Alert & Case Queue

Prioritized by risk score

Auto SAR/STR Narratives

Evidence attached

50+ Regulator Formats

FinCEN, FCA, AUSTRAC

Full Audit Trail

Every alert and filing

Read the docs

aml · case docket3 active

C-2041AML-LAY-12

Layering — wallet cluster

91Investigating

C-2039AML-STR-04

Structuring — cash deposits

78Open

C-2036AML-RTP-09

Round-trip — Nomad LLC

64Filed

SAR narrative · auto-drafted

The subject conducted 4 transactions totaling $58,750 across cross-border wallets exhibiting layering pattern AML-LAY-12 …

FinCEN · FCA · AUSTRAC +50

Trusted & Certified

Built to meet the world's most demanding security and privacy standards.

SOC 2 Type II

Audited security controls for data protection

GDPR Compliant

Full compliance with EU data privacy regulations

ISO 27001

International standard for information security

DIACC Member

Digital ID & Authentication Council of Canada

Integration

Take full control.
Getting started takes minutes.

Plug deepidv into your stack three ways — a REST API, native SDKs, or an MCP server your AI agents can call directly. Clean docs, a sandbox, and one source of truth take you from API key to live verification the same day.

REST API

Call any verification service directly — create a session or run a standalone check and get structured JSON back in under 500ms.

→ screening 200+ watchlists…
✓ status: clear
  risk_score: 4 · 143ms

Drop-in SDK

Pre-built UI components and server libraries for iOS, Android, Web, Node, Python, and Go — zero to live verification in a single sprint.

  checks: ['id','liveness','face'],
✓ v.url → send to your user

MCP for agents

An open protocol that lets any AI agent call deepidv's verification engine directly — no custom integration code. Connect it in one command.

Claude

Launch deepidv for my AI agent — set it up from the docs.

✓ 12 verification tools available

Ready to run ID, liveness & AML checks.

Changelog

The Latest

See all releases

May 18, 2026Release

Verify 2.0 is here

Multi-language verification, a redesigned ID & face-capture flow, end-to-end whitelabel, and a native Background Check step.

May 9, 2026Features

ProofCall, smoother capture & translated reports

AI background-confirmation calls, faster camera start-up, translated PDF/HTML reports, and location-by-IP enrichment.

April 10, 2026AI

AI-powered adverse media screening

Continuous, AI-driven adverse-media checks built natively into your verification workflows.

See all releases

Frequently asked questions

Every transaction is evaluated by our ML scoring engine before it settles. The engine runs multiple models in parallel - behavioral deviation, network analysis, rule matching, and anomaly detection - and returns a composite risk score in under 150 milliseconds.

Behavioral anchoring builds a dynamic profile of each customer's normal transaction patterns - amounts, frequencies, counterparties, geographies, and timing. When a transaction deviates from the anchor, it triggers a risk signal proportional to the deviation.

Our adaptive ML models learn from analyst decisions over time. Combined with behavioral anchoring and network context, the system reduces false positives by up to 85% compared to rule-based systems - meaning your compliance team investigates real threats, not noise.

Yes. The system auto-generates SAR/STR narratives with supporting evidence, formatted for submission to FinCEN, FCA, AUSTRAC, and 50+ other regulators. Reports include full transaction history, risk scores, and investigation notes.

Yes. You can layer custom rules, thresholds, and scenarios on top of our ML models. The system supports jurisdiction-specific rulesets, product-level configurations, and customer segment-based monitoring strategies.

Still have questions?

Our team is ready to help you get started.

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AML Questionnaires

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Transaction Monitoring

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Background Checks

Score every transaction in real time.

See deepidv transaction monitoring on your own data — it takes 60 seconds to start.

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Every transaction.
Scored in real time.