AI workflow reliability for regulated operations

Find the failure before it becomes policy.

Counterproof helps support and operations teams turn promising AI experiments into dependable working systems: scoped, tested, auditable, and usable by the people carrying the pager.

The counterproof method

Build from the exception path inward.

01

Workflow autopsy

Map the real process, including handoffs, unofficial workarounds, missing context, and the points where automation can create a quieter disaster.

02

Reliability scaffold

Design evaluation sets, approval gates, escalation paths, observability, and repair loops around the model rather than trusting the model to become the scaffold.

03

Regulated rollout

Translate constraints into usable runbooks: data boundaries, human review, traceability, ownership, and practical adoption for teams that cannot improvise with sensitive systems.

Best fit

The awkward middle between prototype and production.

Counterproof is for teams with a real workflow, real constraints, and enough AI capability to create momentum, but not yet enough operational structure to trust what they have built.

First engagement

AI Workflow Reliability Review

One workflow. 10 business days. $4,800 fixed fee. Get a record of what the evidence supports, what remains unknown, and which correction or next test is justified.

See scope, deliverables and pricing