Serving, the way agents need it.
Most inference is served for chat: one question, one answer, goodbye. Layer X1's engine was built from the ground up for agents — runs that last hours, hammer tools, and cannot afford a dropped call. You point an agent at the endpoint; the engine guarantees the rest.
Five guarantees, held on every request.
You point an agent at an endpoint. We do the rest. You never see the machinery — you see what it guarantees.
- 01
Always on
Degradation never reaches your run — serving recovers before your agent notices, with no retries to write and no fallback lists to maintain on your side. Zero downtime is the design target, not a status-page apology.
- 02
Fast for agents, from the ground up
Chat inference optimizes one answer. Agent inference is different: hours-long trajectories, tool calls every few seconds, context that keeps growing. Our stack was built for that shape of traffic from day one — sustained throughput across the whole run, not a fast first token and a slow everything else.
- 03
Usage that reads huge
Plans carry a monthly pool of included usage measured in dollars at public list rates — $200 of model usage on a $5 plan, $600 on Pro. Every model in the catalog draws from the same pool: no per-model surcharges, no premium gate, nothing to tune or configure.
- 04
Tool calls that hold
Agent loops live and die on tool calling. The engine enforces strict, schema-faithful tool calls under load, on every model in the catalog, in both agent dialects — so a malformed call never silently derails a run.
- 05
Any agent, no ceremony
Anthropic-compatible and OpenAI-compatible endpoints, streaming everywhere, one key. If it runs an agent loop, it runs here — the engine does not care which framework is driving.
One door. Four protocols.
Whatever dialect your agent already speaks, the endpoint answers it — same key, same catalog, same guarantees. Pick the path your tooling expects and point it here.
Messages
POST /v1/messagesThe dialect agent harnesses like Claude Code speak natively. Swap one base URL and the loop lands here — streaming included.
API reference →OpenAI-compatibleChat Completions
POST /v1/chat/completionsThe dialect nearly every tool ships with. Same key, same models, no SDK changes — if it talks to a chat endpoint, it runs here.
API reference →OpenAI-compatibleResponses
POST /v1/responsesThe newer agent-native dialect used by harnesses like Codex — structured turns and tool calls, streamed end to end.
API reference →OpenAI-compatibleEmbeddings
POST /v1/embeddingsVectors for the retrieval side of your stack, served behind the same key and the same door as everything else.
API reference →Every model, behind one endpoint.
You hold one key and one endpoint — never another vendor account, quota, or bill. Open-weight flagships sit next to premium frontier models behind the same door, and the catalog keeps growing. One key reaches all of it.
Point any agent here in one command.
Run npx layerx1 and pick your tools — the installer writes each config where the tool expects it, key and model included; GUI-configured tools get their exact paste-in values. No SDK, no code changes. The session below is the setup.
Your agent doesn't change.
Everything underneath does.
Start free · no card · Starter from $5/mo