Inference Autopilot

Inference Autopilot is an AI agent that continuously optimizes inference infrastructure to reduce latency, increase throughput, and lower total cost of ownership. It helps teams run multiple models across heterogeneous hardware and cloud environments as traffic patterns and serving requirements change. Powered by GPT-6 Astra, it turns deployment configurations, workload history, and operational telemetry into actionable optimization plans. It identifies bottlenecks, evaluates deployment alternatives, and explains the benefits and tradeoffs of changes to model placement, capacity, batching, and caching—all within the operator’s performance, reliability, and budget constraints. Our goal is to close the loop from observation to verified improvement: monitor the fleet, recommend changes, obtain approval, deploy safely, and measure the results. The hackathon prototype demonstrates this workflow through real Astra analysis, interactive fleet exploration, and simulated blue-green deployments.