Case Study: Outtake achieves scalable, reliable AI-driven cyber threat detection with Inngest

How Outtake's AI Agents Dismantle Cyber Attacks at Scale with Inngest

Outtake, a cybersecurity company, faced the immense challenge of scanning millions of websites and digital surfaces daily to detect fraud and impersonation attacks. Their complex AI agent workflows had to manage numerous rate limits and API throttles while ensuring reliable, durable execution to avoid disruptions. To build this at scale, they turned to the vendor Inngest and its event-driven workflow platform.

By implementing Inngest, Outtake gained durable workflows, sophisticated throttling, and batching features. This provided the robust architecture needed for their AI agents to operate autonomously and reliably. The solution processes hundreds of thousands of attack surfaces daily, successfully reducing threat remediation timelines from weeks to minutes and preventing millions of dollars in fraud losses for their clients.

Outtake

Diego Escobedo

Founding Engineer