The standard

Verifiable Agent Execution.

One question decides whether an enterprise can deploy an AI agent: can you reproduce what it did, prove it cryptographically, and block any unverified change — in your own perimeter, across any model? That standard has a name, and Runback is built to it.

The six properties.

Deterministic replay

Re-run any decision exactly — offline, byte-exact, no model calls.

Re-executable audit

A signed record whose digest the run must reproduce. Verify it, don't just read it.

Language-agnostic capture

Any agent, any language, one base-URL change. No SDK, no support.

Release-gated

Block any agent change that doesn't reproduce the audited baseline, in CI.

In your perimeter

Self-host. Data and prompts never leave your environment.

Model-neutral

Governs whatever you run — GPT, Claude, Gemini, or your own.

Where everyone stands

We don't compete on models. We own the layer above them.

The model labs win on models — and ship evals and tracing. None ship the verification layer, and they're structurally disincentivized to: it commoditizes the model and keeps your data out of their cloud.

Runback
OpenAI
Anthropic
Google
Foundation models
Evals & tracing dashboards
partial
Deterministic replay — offline, byte-exact
Cryptographically-verifiable, re-executable audit
Language-agnostic capture (no SDK)
CI gate — block unverified agent change
Self-host · data in your perimeter
partial
Model-neutral — governs all of them

Honest by design — the labs get every ✓ they've earned. The bottom rows are the standard, and only one column holds them.

Hold your agents to the standard.

See it work on a real run, or read how the verification is built.