Iris 6 is a cloud‑based AML platform that uses machine‑learning and natural‑language processing to automate name‑screening, transaction monitoring and alert resolution. It ingests heterogeneous data, applies dynamic risk scoring to cut false positives by up to 70 % and routes cases through configurable workflows via REST and gRPC APIs, helping banks and fintechs meet AML/KYC and sanctions requirements at scale.
Funding
$40M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
TVFounders
Product
Problem
Financial institutions face high volumes of transactions that must be screened for money‑laundering and related crimes, yet legacy rule‑based systems generate excessive false positives and require extensive manual review, leading to delayed onboarding, operational bottlenecks, and regulatory risk.
Solution
Silent Eight’s Iris 6 platform applies machine‑learning and natural‑language processing to automate the full AML alert lifecycle. The system ingests and normalizes disparate data sources, applies AI‑driven risk scoring to name and transaction streams, and surfaces only the most likely true positives. Integrated AI agents assist investigators by suggesting remediation actions that align with the institution’s risk appetite, while a configurable workflow engine routes alerts through the organization’s existing compliance processes. Results are delivered via a secure cloud service with real‑time APIs, enabling continuous monitoring and rapid response without sacrificing auditability.
Target Audience
The primary customers are banks, credit unions, fintech platforms, and payment processors that must meet AML, KYC, and sanctions compliance obligations while maintaining high transaction throughput.
Features
- AI‑powered name‑screening and transaction monitoring that reduces false positives by up to 70 % compared with rule‑based baselines
- Automated data collection and entity resolution across heterogeneous sources (customer data, sanctions lists, adverse media)
- Dynamic risk scoring models that continuously retrain on new patterns of illicit behavior
- AI‑assisted case resolution agents that generate recommended actions and documentation for investigators
- End‑to‑end workflow orchestration with configurable routing, escalation, and audit trails
- Scalable cloud architecture capable of processing billions of transactions per year with sub‑second latency
- RESTful and gRPC APIs for seamless integration with core banking, KYC, and case‑management systems
- Role‑based access control and end‑to‑end encryption to meet AML‑specific regulatory and data‑privacy requirements