Jancux routes, runs, and observes AI agents across 40+ model providers — behind a single, stable API. Swap models without rewriting your stack.
Python · TypeScript · REST · OpenAI-compatible endpoint
Stop rewriting integrations every time a new model ships. Jancux is the layer that stays stable while the frontier moves.
One endpoint, every provider. Automatic failover when a model degrades, native streaming, and full OpenAI-schema compatibility — drop-in for existing code.
/v1/chat/completionsSet a spend policy per request, per tenant, or per workflow. Jancux picks the cheapest model that clears your quality bar — and shows you what it saved.
Run multi-step agents with tools, memory, and deterministic retries. Long-running tasks survive deploys — state is durable, not held in a request loop.
Every call traced: prompt, model, tokens, cost, latency, tool I/O. Attribute spend to a tenant, a feature, or a single user — no guessing at month end.
Point your existing client at Jancux and keep your model names. Migration is the part we removed.
Replace https://api.openai.com/v1 with your Jancux endpoint. Every existing SDK keeps working — the request and response schemas are unchanged.
Request model: "auto" with a budget and a quality floor. Jancux resolves it per request using live latency, price, and availability across providers.
Traces land in your dashboard within seconds. Replay any call, compare models on your real workload, and change routing rules without shipping code.
| Concern | Direct integrations | With Jancux |
|---|---|---|
| New model support | Rebuild per provider | Config change |
| Provider outage | Your error budget | Automatic failover |
| Cost control | Post-hoc invoices | Per-request ceilings |
| Agent durability | Build it yourself | Durable by default |
| Usage attribution | Manual tagging | Per-tenant, per-call |
You pay a small routing fee on top of provider cost. Scales from a side project to production traffic without a plan change.
Jancux started as internal plumbing. We were running agents across several model providers and kept rebuilding the same glue: retries, fallbacks, cost tracking, tool plumbing. Every new model release meant another sprint of migration work that shipped no product.
So we extracted it. Jancux is that layer, productised — a model-agnostic runtime that treats providers as interchangeable and keeps your application code stable while the frontier moves underneath it.
We are a small, engineering-led team based in Indonesia, building AI infrastructure for teams that need to move quickly without betting their architecture on one vendor.
We onboard a limited number of teams each week so we can support them properly. Tell us what you are building.