MouseCat
AI that
investigates|
like your best analyst
And turns what it finds into features, rules, and better decisions
Built for your entire Risk Team
Scale manual fraud investigations
- Automate research into users and businesses
- Reason and draw connections between disparate data sources
- Complete audit log and explainable decisions
Build better models and rules
- Extract intelligent features from your unstructured data
- Automatically explore and backtest new features and rules
- Generate synthetic labels to find fraud before ground-truth labels
Why MouseCat?
Other AI tools stop at investigations. MouseCat closes the loop from investigation to production rules, models and decisions.
Enterprise Ready
Built for Security
- • On-prem deployment option
- • Customer data stays in your environment
- • Complete audit logs
Works with your stack
- • Connects to Databricks and Snowflake
- • Works with in-house rule engines and feature stores
- • Understands the risk signals you already have
Compatible with
Solutions
KYB Fraud Investigations
- • Deeply interact with business websites, analyze social graphs, and even call business phone numbers
- • Draw connections across all available evidence and surface the riskiest signals
- • Generate explainable decisions with complete audit trails
Automated Rule Development
- • Take an insight from recent investigations and generate a testable hypothesis
- • Select from existing features or craft point-in-time features from your data warehouse
- • Generate a set of candidate rules, backtest against historical data, and surface only high-precision rules
ATO and Payments Fraud Modeling
- • Proactively discover and root-cause anomalies in your training data and inference audit logs: broken features, model drift, or new fraud trends slipping through
- • Generate synthetic labels for ATOs and chargebacks before ground-truth arrives
- • Automatically turn discoveries into backtested features ready for your next model iteration
Founders
Nicholas Aldridge
Co-founder & CEO
Nicholas Aldridge is the Co-founder and CEO of MouseCat, and a core maintainer of MCP. He spent 6.5 years as a Principal Engineer at AWS AI, where he helped launch and lead Amazon Bedrock Knowledge Bases, Agents, and AgentCore. He also represented Amazon on the A2A steering committee. Nicholas has helped some of the largest and most security and privacy sensitive organizations in the world to plan and implement their AI strategies.
Joseph McAllister
Co-founder & CTO
Joseph McAllister is the Co-founder and CTO of MouseCat. Before MouseCat, Joseph spent 4 years at Coinbase building ML and Risk infrastructure, where he focused on streaming systems, large-scale data processing workloads, and improving ATO and ACH risk models. Prior to Coinbase, he worked at Microsoft on Azure Data Factory, a service for building Spark-based ETL pipelines. While studying Computer Science at Cornell University, he founded Roo Storage, which was acquired in 2020.
Get in touch
Ready to transform your fraud investigations? Let's talk.