A growing share of bex router traffic comes from AI agents — trading bots, on-chain research assistants, and autonomous programs that read chain state and submit transactions without a human clicking a button for each call. This guide covers what makes bex router a good fit for that traffic pattern, and what to design around.
Why agents need a metered, multi-chain gateway
A human developer hits a handful of endpoints while building; an agent can call an RPC endpoint hundreds of times a minute, across several chains, with no natural pause between requests. That changes the requirements:
- One key, every chain. An agent that needs to check an Ethereum balance, read a Sui object, and submit an Aptos transaction in the same loop authenticates once — see Overview for the full chain list.
- Cost is machine-readable. Compute units turn "how much did this loop cost" into one comparable number across chains and methods, so an agent (or its budget-tracking wrapper) can meter itself.
- Rate limits are explicit, not discovered by trial and error. An agent that retries blindly on failure can blow through a quota fast; see Rate Limits & Quotas for the numbers and maximizing performance for batching patterns that keep an agent's request volume down.
Designing an agent's request loop
- Batch reads where the chain's API supports it — one batched JSON-RPC call instead of N sequential ones saves both latency and compute units.
- Back off on rate-limit responses — treat a 429 as a signal to slow down, not a transient error to retry immediately; a tight retry loop is the fastest way for an autonomous agent to exhaust a quota.
- Cache what doesn't change block-to-block — chain ID, contract ABIs, and other static lookups don't need to be requests inside the hot loop.
Next step
Understanding compute unit routing covers how bex router selects and monitors the underlying nodes an agent's requests actually land on.