Pricing

Hud is the first Runtime Code Sensor designed specifically to make AI-generated code production-safe by default. It streams real-time, function-level behavior from your live systems into AI development workflows, grounding every code suggestion in the reality of how your software actually runs.

Setup takes less than a minute. Install the SDK and add its init to your code – no configuration or manual instrumentation needed. As soon as it’s deployed, your application’s runtime context begins flowing automatically.

Hud is built for engineering teams using coding agents in their development process (e.g. GitHub Copilot, Cursor, or Windsurf), especially in systems where runtime accuracy, stability, and trust are essential.

Hud enables AI coding tools to generate more accurate, production-ready code by serving them with structured, real-time, function-level runtime data. After installing Hud’s Runtime Code Sensor in production, Hud’s MCP serves AI agents with continuous awareness of how the code behaves in the real world-reducing guesswork and validation cycles.

Hud’s Runtime Code Sensor maps the codebase and tracks function-level behavior inside your live system, to capture anonymized metadata. This metadata includes information about performance, errors, code flows, and more. It is streamed in real time to the coding agent through Hud’s MCP server, where it becomes instantly available to AI agents in the IDE

Hud delivers structured, function-level runtime data that reveals how code actually executes in production. This includes metrics around function usage, execution flow, performance, errors, and behavior drift introduced by new code-all available within your coding environment.

Hud begins surfacing actionable insights within minutes of installation. As soon as the sensor is running, it starts collecting real-time behavior from your functions and delivering that data directly into your IDE or AI workflow.

Hud currently supports Node.js and Python, with support for Java and Go coming soon. It integrates natively with JetBrains IDEs and VS Code, and connects directly to AI development tools like GitHub Copilot, Cursor, and Windsurf through the Model Context Provider.

Yes. Hud is designed to operate across distributed systems and microservices. It tracks function-level behavior across services, surfaces execution regressions, and highlights behavioral changes – all without requiring manual instrumentation or service tracing.

Hud is built with security at its core. It never accesses or uploads source code, payloads, or personal information. The only data transmitted is anonymized function-level runtime metadata. Hud is fully compliant with SOC 2 Type II, ISO 27001, and GDPR, and supports enterprise-grade controls including SAML and SCIM.

Hud is engineered for negligible overhead – typically under 1% CPU – even at scale. It uses lightweight statistical sampling and minimal-footprint logic to ensure consistent performance across high-throughput production environments.

Hud eliminates the need for debugging through logs or dashboards. Developers get immediate insight into how code behaves in production, how new changes impact execution, and where issues are emerging – all directly within their IDE.

Yes. Once installed, Hud runs continuously with no manual configuration, tuning, or operational oversight. It adapts as your application evolves—providing a stable, low-friction source of runtime intelligence from day one.

Hud is essential when teams are shipping AI-generated code into production, scaling agentic development workflows, or validating runtime behavior without relying on dashboards or instrumentation. As systems grow in complexity and autonomy, Hud becomes foundational infrastructure for production-safe software delivery.