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SilkRouter guide

AI agent runtime API for controlled model calls

SilkRouter gives agent builders a gateway for model calls with keys, prepaid credits, routing controls, and usage visibility.

Create agent keyReview routing
How it works

One AI infrastructure control platform, explicit controls, measurable usage

Agents can multiply calls through planning, tool use, retries, and long context. The runtime API layer needs limits, logs, and explicit model choices.

A simple agent can call one provider directly. Production agent workflows benefit from a gateway that helps control spend and diagnose behavior.

Control layer
Keys, routing, balance, reports
Migration check
SDK, model IDs, streaming
First test
One workflow and one key
Benefits

Why teams evaluate this path

Track agent model calls through one API

Use prepaid balance to limit exposure

Separate keys by agent or customer

Monitor failures and token-heavy steps

Decision guide

What to check before production traffic

Compatibility

Confirm SDK behavior, base URL setup, model IDs, streaming, and error handling before moving production traffic.

Operating controls

Check how API keys, balance, request logs, low-balance behavior, and offboarding work after launch.

Reporting workflow

Make sure the usage view answers finance, support, agency, or customer questions without rebuilding data manually.

FAQ

Questions buyers ask before switching

Use these answers to decide what to test, what to keep, and what not to assume before moving production traffic.

Why are agents risky for spend?

They may call models repeatedly, retry failed steps, expand context, or generate long outputs unless controlled.

What should agent logs include?

Track model, status, tokens, billed usage, safe metadata, and enough step context to debug without exposing sensitive user content unnecessarily.

Next step

Create a key and test one workflow.

Start with Research agents and Support agents, then review usage before expanding routing rules.

Sign upCreate API key
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