TESTING

Verifying enforcement not optimizing outcomes.

Verifying enforcement not optimizing outcomes.

Waxell Testing is a pre-production validation environment for agentic governance. It runs the same policies, budgets, and execution logic as production in an isolated sandbox that cannot mutate production state — so you can prove your governance behaves as intended before a single live run depends on it.

Free to start. 2-line setup.

With and Without Testing

With and Without Testing

WITHOUT TESTING

You tighten a policy, ship it, and a customer-facing workflow silently halts in production. You find out from a support ticket — then reconstruct which rule fired from logs after the damage is done.

WITH TESTING

You run the same policy change through production's orchestration paths in an isolated sandbox. You see it blocks too broadly before it ships, and fix the threshold before any production run is affected.

THE PROBLEM

Agentic systems change over time. Policies evolve, budgets get adjusted, execution paths grow more complex. Without a safe way to validate those changes, teams test governance indirectly — by watching production behavior and reacting to failures after they happen. A policy that blocks too broadly or a budget that fires at the wrong threshold becomes a production incident, not a caught bug.

What it is

A sandbox that exercises your real governance plane without touching production. Tests reference the same policies, the same budget limits, and the same execution logic as the live system — and verify behavior, not outcomes. Policies block or allow as defined. Budgets fire at the right threshold. Interrupts, retries, and halts behave as expected.

SEPARATION FROM EXECUTION

Testing authority is isolated from deployment. Tests cannot modify the production governance or execution state they're validating.


Testing authority is isolated from deployment. Tests cannot modify the production governance or execution state they're validating.



OBSERVABILITY AND EVIDENCE

Every test execution produces a persistent, observable result — evidence of what was validated, not an assurance that it was.


Every test execution produces a persistent, observable result — evidence of what was validated, not an assurance that it was.



DESIGNED FOR FAILURE PATHS

Testing deliberately exercises boundary conditions, interruptions, and failure modes — so you understand how governance behaves when things go wrong, before they do.

How it Works

01

Point tests at the real governance plane.

Tests reference the same policies, budgets, and execution logic as production — no separate test definitions to maintain or keep in sync.

02

Run in an isolated sandbox.

Tests execute through the same orchestration paths as production but cannot mutate production state, consume production budgets, or interfere with live execution.




03

Get a durable record.

Every test produces a persistent, inspectable result in Waxell Observe — proof of what was validated, available before you need it.






Get Started

Free to start. 2-line setup.

SOC 2 Ready

Get Started

Get Started

Free to start. 2-line setup.

FAQ

What is AI agent governance testing?

AI agent governance testing is the process of validating that an agentic system's governance controls — policies, budget limits, execution constraints — behave as intended before they go live in production. In Waxell, tests run through the same orchestration paths as production using the same governance primitives, in a sandbox that cannot affect production state.

What can you test with Waxell before going to production?

Teams use Waxell Testing to verify specific governance behaviors: that a policy blocks execution under the right conditions, that a budget limit fires at the correct threshold, and that interrupt and halt behavior works as expected at the workflow level. Because tests run through the same orchestration paths as production, the results are meaningful — not approximations.

Does Waxell Testing affect production systems?

No. Tests run in sandboxed environments that cannot mutate production governance state, consume production budgets, or interfere with live execution. Testing authority is isolated from deployment — tests cannot modify the governance controls they're validating.

FAQ

What is AI agent governance testing?

AI agent governance testing is the process of validating that an agentic system's governance controls — policies, budget limits, execution constraints — behave as intended before they go live in production. In Waxell, tests run through the same orchestration paths as production using the same governance primitives, in a sandbox that cannot affect production state.

What can you test with Waxell before going to production?

Teams use Waxell Testing to verify specific governance behaviors: that a policy blocks execution under the right conditions, that a budget limit fires at the correct threshold, and that interrupt and halt behavior works as expected at the workflow level. Because tests run through the same orchestration paths as production, the results are meaningful — not approximations.

Does Waxell Testing affect production systems?

No. Tests run in sandboxed environments that cannot mutate production governance state, consume production budgets, or interfere with live execution. Testing authority is isolated from deployment — tests cannot modify the governance controls they're validating.

Waxell

Waxell provides observability and governance for AI agents in production. Bring your own framework.

© 2026 Waxell. All rights reserved.

Patent Pending.

Waxell

Waxell provides observability and governance for AI agents in production. Bring your own framework.

© 2026 Waxell. All rights reserved.

Patent Pending.

Waxell

Waxell provides observability and governance for AI agents in production. Bring your own framework.

© 2026 Waxell. All rights reserved.

Patent Pending.