CLEAR Investigate (agentic AI investigations for government, risk and fraud teams) vs Tookitaki FinCense

CLEAR Investigate (agentic AI investigations for government, risk and fraud teams) (Thomson Reuters) and Tookitaki FinCense (Tookitaki) are both listed in the Risk category of Agent Index. They share no framework tags in our dataset. Only CLEAR Investigate (agentic AI investigations for government, risk and fraud teams) is tagged for TX-RAMP.

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Field CLEAR Investigate (agentic AI investigations for government, risk and fraud teams)Tookitaki FinCense
Vendor Thomson ReutersTookitaki
HQ Canada · North AmericaSingapore · Asia Pacific
Primary category RiskRisk
Also listed in Risk, ComplianceRisk, Compliance
Summary Agentic investigation tool built on Thomson Reuters CLEAR public-records data. From a plain-language question it plans and runs searches across CLEAR data and the open web, resolves conflicting records and returns concise cited findings with a record of the searches it ran, for AML, fraud, program-integrity and law-enforcement investigators.APAC AML and fraud platform that combines community typologies with purpose-built AI agents for detection, screening, customer risk and investigation.
Framework tags (Agent Index) TX-RAMP—
Frameworks (vendor-claimed) FedRAMP (In Process)—
Capabilities / tasks case investigation, aml, fraud detection, government complianceaml, fraud detection, kyc, case investigation
Pricing (as published) Not publishedNot verified
Pricing model quotequote
Primary source https://legal.thomsonreuters.com/en/products/clear-investigatehttps://www.tookitaki.com/
Last checked 2026-10-182026-10-18
Official site https://legal.thomsonreuters.com/en/products/clear-investigatehttps://www.tookitaki.com/
Side-by-side data is generated from the open dataset. “Vendor-claimed” frameworks are as marketed by each vendor and not verified by Agent Index; framework tags indicate relevance, not certification. Request current quotes from each vendor before buying. This page does not rank or score vendors. Sponsored comparisons, if any, will be labelled.

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