Automated Red Teaming and Security for GenAI Applications

Repello AI, founded in 2023 in San Francisco, focuses on securing generative AI systems through autonomous threat identification, red teaming, and runtime protection. Its platform is built to expose vulnerabilities in AI models before deployment and enforce adaptive safeguards during operation — an essential capability as organizations integrate large language models and multimodal AI into production workflows.

Repello AI’s automated red teaming engine simulates advanced attacks to uncover logic flaws, jailbreak paths, unsafe outputs, and exploitable model behaviors. These findings feed into dynamic guardrails that continuously enforce security policies with minimal disruption to application performance.

A core strength of Repello AI is its emphasis on context-aware defenses, tailoring mitigations to each model’s architecture, risk profile, and operational environment. The platform leverages self-evolving AI threat intelligence to stay ahead of emerging exploit techniques, enabling it to detect risks even when internal algorithms or training data are

inaccessible. Its solutions integrate naturally into CI/CD pipelines, allowing teams to test, validate, and patch model vulnerabilities early in the development cycle and automatically re-evaluate them as models evolve.

Repello AI works closely with regulated industries such as telecommunications, finance, and healthcare, where AI-driven systems must meet strict compliance and safety standards. Beyond technical defenses, the company invests in community-driven awareness programs — including interactive challenges centered on ethical AI Security — to help expand industry-wide expertise.

The company raised $1.2 million in seed funding in June 2025 from a host of investors, including Venture Highway (acquired by General Catalyst), pi Ventures, Entrepreneurs First and visionary angels.

Repello AI represents one of the earliest specialized players in AI offensive security. Its work underscores a central theme of this book: as generative models reshape digital infrastructure, organizations need autonomous systems capable of probing, hardening, and governing AI at the same speed with which it learns and adapts.