Chimera

What if your code could fix itself—and make itself faster while doing it? Our project is an AI-driven self-healing pipeline that works on two levels: it not only automatically optimizes GPU configurations for any GitHub repository, tuning kernels, thread blocks, and memory usage to achieve maximum performance, but it also detects, diagnoses, and fixes software issues in real time. Today, software teams spend 40–60% of their time debugging, profiling, and resolving production errors instead of building new features. Our system solves that by combining four autonomous agents: one that monitors GitHub repositories and Datadog alerts, one that reasons about issues using OpenAI to generate intelligent fix proposals, one that executes those fixes safely in sandboxed TrueFoundry environments, and one that deploys validated solutions back to production. The result is a continuous loop of optimization and recovery—code that learns from its own performance and failures. We’ve already integrated with TrueFoundry, Datadog, and GitHub APIs, demonstrating how the system can analyze public repositories, identify bottlenecks, test improvements safely, and deploy validated fixes automatically. Instead of engineers spending hours debugging failed CI/CD pipelines or tuning GPUs manually, our system does it in minutes—like having a 24/7 senior DevOps and GPU engineer that never sleeps. We’re now seeking early adopters to pilot this technology and cut incident-response and optimization times from hours to minutes. Because in our vision, your code should work for you, not against you.

Built With

• chatgpt
• cursor
• datadog
• openhands
• python
• truefoundry