Banking (AML & Financial Crime)
How a major financial institution automated 80% of analyst hands-on AML time by deploying AI inside its own secure infrastructure.
Read the Case Study80%
AML analyst hands-on time automated
Capabilities
Reasoning you can defend, at institutional scale.
Kundi applies the same analysis to every case, document and record in scope, and shows the evidence for each conclusion.
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over 1,000 Algorithms
A coordinated system drawing on over 1,000 algorithms applies the same reasoning across every case.
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Connected Signals
Connects signals across documents, records, and datasets, and evaluates context, relationships, and implications to form clear conclusions.
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Consistent Logic
Applies the same logic to ambiguous inputs every time, and routes the cases that need judgment to a person.
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Full Coverage
Reads entire document corpora and analyzes full transaction and case volumes, for full coverage instead of partial review.
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Patterns and Hidden Risk
Identifies patterns and anomalies across the full data set, not a sample.
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Action-Ready Outputs
Produces structured outputs ready for action, so teams focus on judgment, not throughput.
How Kundi is built
One component per layer, each one improving the platform.
Kundi has three components: Conductor for applications and workflows, COSMIC for algorithms, and Tarn for data and policy.
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Conductor · Workflows
AI agents design, test and refine workflows, with a full record of every input, computation, model call and decision.
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COSMIC · Algorithms
A nightly research engine that adds tested algorithms to a library of over 1,000, implemented independently in Ada, C, C++, COBOL, Erlang, Python and Rust.
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Tarn · Data and Policy
A full data lakehouse and warehouse that can be used in place of Snowflake or Databricks. It drafts regulatory policy updates for approval and enforces them once approved.
Product tour
See Kundi work.
Click a window, or its green button, to read it full-screen.
01 · COSMIC · Algorithms COSMIC (part of Kundi): Verified Algorithms
02 · Tarn · Data and Policy Tarn: Governed Data Platform
Deployment & Security
Deterministic, auditable, and quantum-resilient by default.
Kundi operates inside institutional environments by default. Analytical execution is deterministic, and any governed query can be replayed against the data and policy in force at the time.
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Inside Controlled Infrastructure
Runs within controlled infrastructure, and a secure ingestion architecture ensures institutional data flows safely into the system, for scalable intelligence within controlled environments.
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Your Models and Weights
The models and weights stay yours, including any improvement derived from your data.
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Auditable Reasoning
Outputs and reasoning are logged for auditability and support executive, legal, and regulatory review, so outputs withstand scrutiny and decision-making stays aligned to institutional requirements.
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Quantum-Resilient
Post-quantum cryptography ships as standard, inside your infrastructure: PQC-native key establishment and signatures, with long-lived records protected against harvest-now, decrypt-later.
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Crypto-Agile
Post-quantum cryptography is standard. See Security & Compliance for algorithms and verification.
Kundi in Production
Product Walkthrough
See it inside your environment.
Live Kundi walkthroughs in your environment are available under NDA. Request a briefing to see the actual workspace, governance controls, and audit trail running against your data, infrastructure, and compliance posture.
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