The confidence you need.
The control you require.

01 / The evidence

Value depends on the work.

Research has found both improvements and slowdowns. The useful question is what changes in your workflow, with your data and your requirements.

Different studies and measures, shown separately. These are external research findings, not Pathsum results or forecasts. METR’s February 2026 follow-up reports selection effects that limit conclusions about newer tools.

02 / The controls

Build the checks into the work.

PathLAB Studio brings workflow controls, execution records and experiments into one workspace. These are the product’s intended capabilities; Studio is pre-release and unavailable to use.

Define the workflowPathPLAN

Make the steps, inputs and required checks explicit before a run.

Limit what can happenPermissions & limits

Set which tools a workflow may use and where it must stop.

Keep people in controlHuman approval

Require a decision before a consequential action can continue.

Inspect what happenedPathPROOF

Keep the route, results and checks together in a verifiable execution record.

Test an improvementExperiments

Compare changes against the same cases and requirements, including cost and review effort.

Keep useful evidenceDatasets

Choose which reviewed examples become test cases or data for further work.

A verifiable record shows what happened. It does not establish that the source data or answer was correct. NIST’s AI Risk Management Framework provides guidance for managing and evaluating AI risks; this is not a claim of certification.

03 / Your starting point

Bring the problems. Look at the evidence.