Which strategies slipped past our verifiers? Read the adversarial audit →

Find the failure. Build the environment. Grade the work. Sign it off.

Diagnosis, environments, verifiers, and pre-deployment evidence across the full arc of agent work.

We work across the whole arc of agent work: finding where a model breaks down in a real workflow, building the environment that reproduces it, grading the work against the records rather than the summary, and handing over the evidence before anything touches production.

01 · Diagnose

Failure-mode studies and held-out task sets

We find where an agent breaks down in a specific workflow, then turn each failure into a task that can be scored.

  • Tasks written by people who have done the work, not by annotators approximating it.
  • Each task carries its own ground truth, so a score points at one named failure rather than a percentage.
  • Delivered as a task set you can re-run against every checkpoint, model, and vendor.
Why invariantsNote · DraftRead the note ↗

02 · Simulate

Environments and scenario generators

The workflow rebuilt as a stateful system the agent can act inside, and a generator that seeds as many variants of it as a training run needs.

  • API, UI, and MCP surfaces over the same state, so one environment serves tool-calling and computer-use training.
  • Resettable and snapshot-able. A failed run can be replayed from the step before it went wrong.
  • Describe a company in plain language and get a seeded business: open items, a half-finished period, a reconciliation that does not tie.
Browse the environment catalogueNote · DraftRead the note ↗

03 · Verify

Verifiers, invariants, and adversarial audits

Grading against the records themselves. We attack our own verifiers first and publish which strategies got through.

  • Invariants checked across the whole trajectory, not only the final state, because the right end state can be reached by the wrong actions.
  • Expert rubrics only where the work genuinely calls for judgment, kept separate from the deterministic layers.
  • Every verifier ships with the round it failed, the constraint we added, and the results of running again.
Attacking a graderNote · DraftRead the note ↗

Every layer we grade at

L0 · Hard invariants

Identities that cannot be violated in any valid state. Purely programmatic.

L1 · Business correctness

Right period, right account, right counterparty, complete document chain.

L2 · Process compliance

Authority, self-approval, workflow bypass, forbidden side effects. Judged from the event log.

L3 · Judgment

Whether an estimate is reasonable and an assumption holds. Expert rubric, scored separately.

Evidence

Each action tied to the record that supports it. Missing evidence is a failure, not a deduction.

Determinism

The same trajectory scored twice returns the same result, or the verifier is the defect.

04 · Certify

Evidence before production access

What an enterprise needs in order to sign off: the full record of what the agent did, and what it was not allowed to do.

  • Every tool call, side effect, and state change captured, with forbidden effects counted rather than described.
  • Private task sets covering the exceptions that matter to one firm, held out from anything published.
  • A pre-deployment report a reviewer can read end to end, with full replay of any run in it.
Expert trajectoriesNote · DraftRead the note ↗

Delivered as

One asset, several deliverables.

RL environmentsEvalsExpert trajectoriesSFT dataRubric dataPrivate benchmarks