AI startup Tangos raises $20 million for AML tools

Tangos, an AI-powered startup that builds software to detect financial crime, announced it has raised $20 million to scale its platform for detecting and investigating money laundering, fraud and other illicit financial activity.

According to the company, the platform combines transaction monitoring, entity-relationship analysis and automated investigation workflows. Its algorithms analyze transaction flows, account behavior and network connections and generate alerts with contextual information intended to help analysts prioritize and investigate cases. The system integrates with existing transaction monitoring and case-management tools.

The company announced the funding will support product development and commercial expansion. The round included venture capital and strategic investors, though the company did not disclose a full list of participants. Tangos plans to expand engineering and product teams, hire sales and customer-success staff, and work on additional data sources and model explainability features.

Regulatory expectations for anti-money-laundering programs have increased demand for automated tools that can handle large transaction volumes and complex networks. According to Tangos, its machine-learning and graph-analytics approaches complement rule-based systems and aim to lower false positive rates and speed investigations.

The startup competes with established transaction-monitoring vendors and newer firms focused on applied machine learning and network analytics. Tangos targets customers with high transaction throughput and complex counterparty relationships. The company reports ongoing pilots and deployments with banks, payments firms and digital-asset custody providers, and plans to expand its commercial footprint in additional regions over the coming year.