Machine-native routing for AI agents

One task in. An eligible provider out.

ATL discovers and verifies providers, applies lifecycle and Gate checks, returns a primary route and fallback when available, and learns from real execution outcomes.

Try a routeSee measured production resultsConnect in 30 seconds
1. Describe the taskNo provider identity required.
2. ATL checks eligibilityHealth, freshness, policy, budget and Gate.
3. Get primary + fallbackBounded failover route when available.
4. Report the outcomeFeed real latency, cost and success back.
Measured on the public production path · 2026-09-25

Less routing overhead. Smaller machine responses. Fail-closed behavior preserved.

After the first Decision hot-path performance pass, ATL was benchmarked from an external GitHub-hosted runner against the public production endpoint. These are measured results from that test set, not theoretical projections.

~1 msInternal Decision latency observed in the production comparison request.
1.75 sMedian external round trip from the GitHub runner to the public ATL endpoint and back.
91.3%Smaller serialized Decision response body with compact mode: 9,033 B → 783 B.
16 / 1612 supported routes returned the expected primary + fallback; 4 unsupported capabilities returned NO_MATCH.

Scope matters: the 91.3% figure is response-body reduction for this benchmark, not a claim about model tokens or total application bandwidth. The 16/16 figure describes this test set, not universal accuracy. Read the benchmark methodology and caveats.

Live Route Demo

Send a real Decision request to ATL's production entrance. The first production-tested public capability is summarize. The demo uses compact mode to minimize machine-response bytes.

Task
Ready.
Decision
Run a route to see the selected provider, alternatives and decision reference.

Connect where you already build

MCP

https://mcp.agenttrafficlab.com/mcp

Use atl_decide and atl_report_outcome.

Python

from agenttrafficlab import decide\n\nroute = decide("summarize this ticket")

Zero runtime dependencies.

JavaScript

import { decide } from "@agenttrafficlab/client";\n\nconst route = await decide("summarize this ticket");

Node.js 18+.

Why ATL exists

Not just model aggregation

ATL is focused on route eligibility, lifecycle state, Gate checks, authorization, bounded failover and outcome evidence.

Fail closed before routing

A provider is not treated as production-eligible just because an endpoint exists.

Machine traffic first

The target is agent-to-infrastructure traffic, not a dashboard that humans must operate manually.