Also known as: Agnostic
AI-powered toolkit for risk teams to detect, investigate, and mitigate fraud trends.
Risk teams face challenges scaling manual fraud investigations, building effective models from unstructured data, and responding quickly to emerging fraud trends.
Risk teams face challenges scaling manual fraud investigations, building effective models from unstructured data, and responding quickly to emerging fraud trends.
AI toolkit that automates investigations, extracts features, backtests rules, generates synthetic labels, and integrates with enterprise data stacks for faster, explainable decisions.
AI toolkit that automates investigations, extracts features, backtests rules, generates synthetic labels, and integrates with enterprise data stacks for faster, explainable decisions.
Appears active as of Winter 2026 based on Y Combinator listing and company website.
Event Year: 2026
Appears active as of Winter 2026 based on Y Combinator listing and company website.
Event Year: 2026
MouseCat offers an AI-powered toolkit tailored for risk teams. The platform automates the detection, investigation, and mitigation of emerging fraud trends. It supports scaling fraud investigations, building improved models, and enabling faster decisions based on available information from company sources.
MouseCat focuses on key functions for risk operations. It automates research into users and businesses, reasons across disparate data sources, and provides complete audit logs with explainable decisions. The tool extracts intelligent features from unstructured data, explores and backtests new features and rules, and generates synthetic labels to identify fraud ahead of ground-truth labels.
For KYB fraud investigations, MouseCat interacts deeply with business websites, analyzes social graphs, and even calls business phone numbers. It draws connections across evidence to surface riskiest signals and generates explainable decisions with audit trails. In automated rule development, it turns insights from investigations into testable hypotheses, crafts point-in-time features, backtests rules, and surfaces high-precision options.
MouseCat offers an AI-powered toolkit tailored for risk teams. The platform automates the detection, investigation, and mitigation of emerging fraud trends. It supports scaling fraud investigations, building improved models, and enabling faster decisions based on available information from company sources.
MouseCat focuses on key functions for risk operations. It automates research into users and businesses, reasons across disparate data sources, and provides complete audit logs with explainable decisions. The tool extracts intelligent features from unstructured data, explores and backtests new features and rules, and generates synthetic labels to identify fraud ahead of ground-truth labels.
For KYB fraud investigations, MouseCat interacts deeply with business websites, analyzes social graphs, and even calls business phone numbers. It draws connections across evidence to surface riskiest signals and generates explainable decisions with audit trails. In automated rule development, it turns insights from investigations into testable hypotheses, crafts point-in-time features, backtests rules, and surfaces high-precision options.
B2B
B2B
Risk teams in organizations dealing with fraud, including fintech and enterprise security operations.
Risk teams in organizations dealing with fraud, including fintech and enterprise security operations.
Active YC Winter 2026 batch with live website.
Hiring: No hiring indicated; team size 2.
Active YC Winter 2026 batch with live website.
Hiring: No hiring indicated; team size 2.
MouseCat addresses ATO and payments fraud modeling by discovering anomalies in training data and inference logs, such as broken features or model drift. It generates synthetic labels for ATOs and chargebacks and turns discoveries into backtested features for model iterations. This closes the loop from investigation to production rules and models.
MouseCat addresses ATO and payments fraud modeling by discovering anomalies in training data and inference logs, such as broken features or model drift. It generates synthetic labels for ATOs and chargebacks and turns discoveries into backtested features for model iterations. This closes the loop from investigation to production rules and models.
Designed for enterprise use, MouseCat offers on-prem deployment to keep customer data in the environment. It provides complete audit logs and integrates with stacks like Databricks and Snowflake. It works with in-house rule engines, feature stores, and existing risk signals. Compatibility extends to tools such as Middesk, Sardine, Socure, Persona, Alloy, Ekata, LexisNexis, and Seon.
Designed for enterprise use, MouseCat offers on-prem deployment to keep customer data in the environment. It provides complete audit logs and integrates with stacks like Databricks and Snowflake. It works with in-house rule engines, feature stores, and existing risk signals. Compatibility extends to tools such as Middesk, Sardine, Socure, Persona, Alloy, Ekata, LexisNexis, and Seon.
Unlike other AI tools that focus solely on investigations, MouseCat extends to production rules, models, and decisions. It emphasizes security, privacy, and seamless workflow integration for risk teams handling complex fraud challenges.
Unlike other AI tools that focus solely on investigations, MouseCat extends to production rules, models, and decisions. It emphasizes security, privacy, and seamless workflow integration for risk teams handling complex fraud challenges.
Founded by experienced professionals in AI and risk. Nicholas Aldridge, Co-founder and CEO, brings expertise from AWS AI, including Amazon Bedrock. Joseph McAllister, Co-founder and CTO, has background from Coinbase in ML and risk infrastructure, plus Microsoft and an acquired startup.
Founded by experienced professionals in AI and risk. Nicholas Aldridge, Co-founder and CEO, brings expertise from AWS AI, including Amazon Bedrock. Joseph McAllister, Co-founder and CTO, has background from Coinbase in ML and risk infrastructure, plus Microsoft and an acquired startup.
