Value Creation Diagnostic

For COOs, CFOs & Operations Leaders

Move AI automation out of pilot purgatory and into daily operations

We map the manual work and choose the automation targets that can survive production. Then we deploy AI and RPA, with human review, in workflows operators can trust.

See the AI-for-EBITDA Framework Start With a Process Assessment
Graphite sketch of a workshop jig holding a wooden piece beside an inspection square.

Our approach

We redesign the workflow before choosing the tooling

Most automation projects stall because nobody settled the workflow and data questions, or who owns the result. We start there. We redesign the workflow and put the data and exceptions in order. Only then do we choose the automation patterns that can run in production.

We strengthen sponsor and management-team execution capacity. We do not replace operations, finance, or customer-team judgment.

What the work supports

Four things an automation program has to deliver

Operational Throughput
Manual queues and review loops moved into trusted production workflows, with exception handling built in.
Operator Trust
Human-in-the-loop design so the operations team can rely on the output, and so can finance and customer teams.
Reporting and Visibility
Cycle-time and exception signals surfaced to the operating cadence and the board, with quality signals alongside them.
Tech and Vendor Discipline
Sensible tooling choices that fit the workflow instead of chasing every AI vendor demo.

How we sequence the work

From workflow discovery to automations in production

  1. Days 1–10

    Workflow discovery

    Map the manual work and exception queues that actually drive cost and cycle time. Follow them through finance and customer ops into the reporting steps.

    Outcome

    A prioritized list of workflows, each with a named owner. Source systems and decision points are mapped for each one.

  2. Weeks 2–3

    Design for production

    Combine workflow redesign and data readiness with the right mix of AI assist, RPA, low-code and human-review patterns. The result is a buildable plan.

    Outcome

    A plan operators can sponsor, built to get past the vendor-demo stage.

  3. Weeks 3–8

    Build and instrument

    Implement automations in scoped sprints. Telemetry and exception handling go in from day one, along with quality checks.

    Outcome

    Working automations in production with reporting the operator can defend.

  4. Weeks 8+

    Operate and extend

    Tune precision and expand to adjacent workflows. Signals feed back into the operating cadence and KPI layer.

    Outcome

    An automation footprint that keeps compounding instead of decaying after launch.

Service focus areas

Where we build automation

  • Workflow Redesign and Automation Strategy
  • GenAI and LLM-Assisted Operator Workflows
  • RPA and Low-Code Automation
  • Finance and Customer Automation
  • Back-Office Automation

Common next routes

Bring the manual workflow or the reporting gap

In a diagnostic conversation, we will help identify the first automation worth building into production.

Request a Value Creation Diagnostic