Forward-deployed delivery

From workflow discovery to production, with the same team.

Our engineers work directly with the people who own the workflow. We do not wait for a perfect requirements document and disappear after a handoff. We discover, design, build, integrate, launch and improve the system with your team.

Delivery phases

Six phases, each with an output you can hold us to.

1

Discover

Shadow the workflow. Establish volume, systems, decisions, exceptions, owners and constraints, and what the current state costs.

OutputCurrent-state workflow and a defined opportunity
2

Design

Choose where AI helps, where rules stay deterministic, and where humans must stay in control. Agree the access model.

OutputTarget workflow, architecture and acceptance criteria
3

Build and integrate

Implement the model or agent logic, backend, APIs, state, permissions, interface where one is needed, and the system integrations.

OutputA working production candidate
4

Evaluate

Test historical and live cases, edge conditions, failure handling, quality, latency, cost and safety before anything is trusted.

OutputEvaluation report and a launch decision
5

Deploy

Roll out to a bounded team or workflow and instrument the process so the operation can be watched from day one.

OutputA production workflow
6

Operate and improve

Review exceptions, adoption and business outcomes. Improve in production, then expand to the next workflow when it has earned it.

OutputOngoing improvement, or the next workflow
The part most vendors skip

We do not automate the happy path and leave your team with the failures.

The failure surface is where an operational system is won or lost. It is designed at the start, not patched after go-live.

Exception queues and escalation paths

Every case the system cannot finish has a named destination and an owner.

Human approvals where risk requires them

Placed by risk and uncertainty, not spread evenly to look safe.

Audit trails

What the system did, on what evidence, and what a person decided instead.

Fallback behavior

Defined for the moment a model, tool or integration fails, because one of them will.

Operational dashboards

Throughput, failures and pending work, visible to the people accountable for them.

Evaluation before and after deployment

A measured baseline, then continuous measurement against it.

Exception queueIllustrative
  • Missing purchase order referenceRequired field absent on intakeAwaiting approval
  • Supplier name disagrees across documentsCross-document check failedRouted to ops review
  • Address change appliedPassed all checksWritten to system of record
  • Refund above autonomy thresholdBounded action limit reachedEscalated to a person

Every item carries the reason it stopped and who owns it next. That is the difference between a queue and a backlog.

Engineering principles

How we make the calls, before you have to ask.

Workflow first, agent second

The operating model is the design. The agent is one component inside it.

Deterministic where possible

If a rule can do it correctly, a rule does it. Models are used where judgment is genuinely required.

Autonomy is bounded explicitly

Every action the system can take is a decision someone made on purpose.

Stateful and resumable

Long-running work survives failure, restart and retry without duplicating actions.

Escalation is a feature

Handing a case to a person is a designed outcome, not an error state.

Evaluation before scale

Nothing widens until there is a number that says it should.

Operational visibility by default

If the operation cannot be seen, it cannot be owned by the people who run it.

Model-agnostic

Components are replaceable. We do not build a dependency on one provider into your operation.

Security follows the action surface

Access is scoped to what the workflow does, and reviewed when the workflow changes.

Designed for replacement

Your team can take it over. Documentation and handover are part of the work, not an upsell.

Working together

What we need, and what you get back.

What we need from you

  • One owner of the workflow who can answer questions and make calls
  • Access to the systems involved, at the level the scope requires
  • Real cases, or a redacted sample that behaves like real cases
  • A short weekly review while the engagement is live

What you get from us

  • A named engineer, not a rotating pool
  • Agreed live overlap hours and response expectations before kickoff
  • Working software in your environment, not slideware
  • A written record of decisions, scope and what was deliberately left out

Bring us one workflow that should work better.

Twenty to thirty minutes to understand how it runs today. If there is nothing worth deploying, we will say so.

Discuss a Production Problem