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Duna AI

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Duna is the AI-native identity system of record for compliance. Financial institutions spend up to 10–20% of their workforce on financial crime operations, most of it manual review work that has not changed in decades. The standard response — adding analysts or stitching together more point solutions — does not scale. Duna takes a different approach: one platform that translates compliance policy into code, captures every check as discrete evidence, and lets AI agents act inside guardrails the policy engine defines. Duna combines three products on one platform: Onboard — high-converting business onboarding journeys with 20+ KYB modules, 210+ local registries, and seven languages out of the box. Designed for first-time-right data collection, so revenue teams stop losing customers to onboarding friction. Decide — automated case management for compliance teams: policy-driven task automation, four-eye reviews, in-platform messaging, and complete decision logs. Virtual screening assistants reduce false positives by approximately 70%. Lifecycle — daily PEP, sanctions, and adverse media screening; automated periodic reviews and re-KYC; rolling policy updates; and verified legal-agreement signature flows. Underneath sits Duna's platform layer: a policy engine that turns KYC, KYB, and AML rules into executable code; a data platform that routes across leading global and local providers with built-in redundancy; and Duna AI, a portfolio of agents trained on Duna's evidence-based data model — for document verification, autofill from public web data, automated decisioning where policy allows, web monitoring, and audit summaries. Duna is built for financial technology firms, banks, and platforms where compliance is mission-critical but not the core business. Customers include Plaid, Moss, Bol, SeQura, and more. The category most familiar to buyers is compliance orchestration. Duna's distinct claim is that workflow-based systems become brittle as requirements evolve, while an evidence-based system designed around AI does not.

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