Protect Crypto Assets with Governed AI
Rapid growth across crypto markets, rising transaction volumes and expanding regulation place additional pressure on Elliptic’s clients: compliance teams at exchanges, banks, payment providers and institutional custody platforms. Even with robust risk scores and comprehensive screening results, compliance analysts must document their decisions by bringing together information on exposure values, crypto assets, addresses and the chronology of transactions. This makes it harder to scale rapidly without increasing costs.Elliptic helps compliance analysts spend less time triaging alerts and more time making consistent decisions as crypto adoption drives higher alert volumes, without lowering the bar for regulatory readiness. “Clients need clear, report‑ready narratives that can stand up to regulatory scrutiny,” said Amar Chandarana, Senior Product Manager at Elliptic. “Elliptic’s copilot analyzes and summarizes wallet and transaction activity, highlighting critical exposure and providing relevant risk context for faster decision-making.” Applying large language models (LLMs) to these workflows introduces new challenges, especially in sensitive domains like sanctions, terrorist financing and child exploitation. Compliance teams needed strong assurances that Elliptic’s copilot would not hallucinate, omit key context, or rely on opaque reasoning, particularly when its outputs might feed into formal investigations and regulatory reports.To address this, Elliptic used Databricks tooling to make every response traceable, evaluated and governed. MLflow tracing captures prompts, intermediate steps and final narratives for each interaction, so that if an issue is reported, Elliptic's team can quickly understand how a response was created and what information was provided to the model. Elliptic has defined domain-specific safety guidelines to distinguish between describing financial crime typologies and inadvertently mentioning harmful activity, ensuring Elliptic's copilot explains patterns related to money laundering or sanctions in neutral, factual language tied to on-chain evidence and internal risk models. This combination of traceability, automated evaluation and domain-tuned safety controls allows Elliptic to deploy LLMs in high-stakes compliance workflows with confidence that outputs are consistent, defensible and suitable for regulator-facing use cases.
