Care in the process.
Confidence in the system.
A convincing demo is a beginning. A dependable workflow also needs good data, explicit permissions, tested exceptions, and a team that knows how to run it.
Find the friction
Map the real workflow. Measure the current effort and identify one useful place to start.
Output / A clear business caseBuild with intention
Connect the right systems. Define the rules, review steps, and failure behavior.
Output / A controlled pilotProve it in practice
Test against representative work. Start with human review and measure the difference.
Output / An evidence-led rolloutMake it yours
Train your team, document the system, and agree how it will be operated and improved.
Output / A system you can ownBuilt for the days
that don’t go to plan.
We sample real work and agree the baseline, eligible cases, and acceptance criteria with a process owner.
Use ordinary rules for arithmetic, matching, permissions, and limits. Use AI where interpretation adds value.
Keep credentials server-side, use minimal permissions, and separate client, test, and production data.
Retain source references and record which policy, document, or system state informed the next action.
Bind approval to a specific action and record version. Recheck state before execution.
Deduplicate incoming work, bound retries, and reconcile against the destination system.
Measure the final business state, quality, latency, and cost against representative and adversarial examples.
Provide runbooks, alert routes, ownership, training, and a manual recovery path.
What we need
from your team.
- 01A process ownerSomeone who understands the work and can approve policy and acceptance criteria.
- 02Representative examplesRedacted historical inputs, typical exceptions, and expected outcomes.
- 03Supported system accessAn administrator to arrange appropriate API permissions or imports.
- 04Time for evaluation and adoptionOperators to review output, provide corrections, and learn the new workflow.
Practical standards.
Honest claims.
Our design principles draw on established engineering and risk-management guidance. They are not a claim of certification, an audited compliance status, or a guarantee that every workflow is appropriate to automate.