MouseCat Analysis
What is MouseCat?
MouseCat builds agentic AI infrastructure for risk operations teams handling fraud investigations. The platform runs inside customer cloud accounts and uses agents, prompts, tools, and evaluation pipelines to automate case review. It reports private beta results including 81 percent precision and 77 percent recall at a $50B plus global marketplace, plus $1.5M monthly fraud losses prevented at a crypto exchange.
Location
New York, NY, USA
Employees
1-10
Founded
2026
Business Model v4
Fintech
Delivery Model
Services-as-software (AI-native service)
Functional Type
Compliance Tech,AI-Driven Threat Detection & Response
YC Batch
W26
YC Partner
Jared Friedman
Product Features & Capabilities
- Automated fraud investigation tools
- Feature extraction from unstructured data
- Rule development and backtesting
- Synthetic label generation for fraud detection
- Audit logs for decision-making
Use Cases
Automate user and business research for fraud; Generate testable hypotheses from investigations; Backtest candidate rules against historical data; Discover anomalies in training data; Create synthetic labels for fraud detection
Product Description
MouseCat offers AI-powered tools specifically designed for fraud investigations, targeting risk teams in financial services. Their main product features include:
- Automated Research: This feature allows teams to automate the research process into users and businesses, significantly scaling manual fraud investigations.
- Feature Extraction: MouseCat's tools can extract intelligent features from unstructured data, which aids in building better models and rules for fraud detection.
- Explainable Decisions: The platform provides a complete audit log and ensures that decisions made during investigations are explainable, enhancing transparency.
- End-to-End Investigation: Unlike many other AI tools, MouseCat closes the loop from investigation to production rules, models, and decisions, making it a comprehensive solution for fraud detection.
These features collectively enable risk operations teams and data scientists to improve their fraud detection capabilities and compliance efforts.
Other Considerations
Backed by Y Combinator; Founders with experience at AWS and Coinbase; Significant metrics include 10x more investigations closed and 85% reduction in manual review
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