BytesBrains Cruise: A job ID that never goes stale. Fallback across AI models.

Hey Product Hunt! 👋 I'm Sandeep, maker of BytesBrains Cruise. We built Cruise out of a very real, frustrating bottleneck: our agentic pipelines were completely built, working, and deliberately switched off. Why? Because an autonomous agent loop with no hard budget ceiling is an unbounded financial liability. When you manage accounts across OpenAI, Anthropic, DeepSeek, Google, and others, three things happen: 1. Credentials sprawl across repos and get rotated manually. 2. Answering "what did project X spend last month by model" requires reconciling half a dozen dashboards with different billing granularities. 3. If an upstream provider rate-limits or has an outage mid-run, your user experiences a crash. Cruise is our answer: cruise control for AI APIs. 🏎️ What makes Cruise different: • One OpenAI-compatible drop-in: Just swap your `baseURL` and keep your existing SDK code. • Intent-based Lanes & Fallback: Route by job/intent rather than hardcoded model names. If a provider rate-limits (429) or goes down (500), Cruise instantly falls back to an equivalent model without failing the job. • Spend control that unblocks the work: Hard per-project budget ceilings and a real-time ledger down to the request. You can unleash autonomous agents without dreading an unexpected bill. • Zero-redeploy retuning: Switch models, weights, or fallbacks in your control plane without redeploying code. You can try it live without even creating an account or providing an API key on our demo endpoint at https://cruise-demo.bytesbrains.... I’d love to hear how your team currently handles multi-provider fallbacks and API spend governance. Any feedback, questions, or feature requests are warmly welcomed!