How it works

From a stuck workflow to a tested one.

GreyShacks assesses one workflow, names what blocks reliable completion, and defines a realistic autonomy target. Engineering, validation and improvement follow only for the stages you commission.

Six stages. You can stop after the first.

Assess, identify blockers, define the target, engineer, validate, then operate and improve. The assessment is useful on its own.

  1. 01

    Assess

    Select one workflow. See how it runs, where AI is already used, and where people still intervene.

  2. 02

    Identify blockers

    Trace missing information, system limits, unclear rules, integration gaps, exceptions and unresolved risk.

  3. 03

    Define the target

    Decide what can run autonomously, what stays under human control, and which technical changes are required.

  4. 04

    Engineer

    Implement the workflow, agent capabilities, integrations, permissions, exception handling and tests the blueprint calls for.

  5. 05

    Validate

    Run complete business cases, including abnormal ones. Check the outcome, and whether routine intervention has decreased.

  6. 06

    Operate and improve

    Monitor outcomes, investigate failures, keep the controls current, and change the system as the business changes.

How we decide

One workflow, with an owner

We start with a process that has a trigger, a volume of work, existing systems, recurring human intervention and someone accountable for the outcome.

Evidence before a target

The diagnosis separates what the operation can show from assumptions and from scenarios that still need a test.

Autonomy has a boundary

The target says what can run on its own, what needs approval, and what is not ready. Full automation is not the default.

Engineering follows the blockers

The build includes the workflow changes, integrations, rules, tests and controls this process needs. It does not include a capability the assessment did not justify.

Validation uses the whole case

A step that succeeds in a demo is not acceptance. We test normal cases, variations, failed actions and the business outcome.

The assessment can stand alone

You can take the written diagnosis and decide later whether to commission implementation or ongoing improvement.

What each stage produces

Each stage has a tangible output. Later stages use the diagnosis from the assessment.

01

Assess

Select one workflow. See how it runs, where AI is already used, and where people still intervene.

You receive: A current-state workflow and an evidence-backed diagnosis.

02

Identify blockers

Trace missing information, system limits, unclear rules, integration gaps, exceptions and unresolved risk.

You receive: A prioritized list of blockers, with evidence and open questions.

03

Define the target

Decide what can run autonomously, what stays under human control, and which technical changes are required.

You receive: An autonomy blueprint and measurable acceptance criteria.

04

Engineer

Implement the workflow, agent capabilities, integrations, permissions, exception handling and tests the blueprint calls for.

You receive: A working solution ready for controlled validation.

05

Validate

Run complete business cases, including abnormal ones. Check the outcome, and whether routine intervention has decreased.

You receive: Documented results against the baseline and acceptance criteria.

06

Operate and improve

Monitor outcomes, investigate failures, keep the controls current, and change the system as the business changes.

You receive: An operating model with measurable performance and a named owner.

Start with one workflow.

Show us a process where AI still depends on people to gather information, make routine decisions, move between systems or finish the work. We will assess what is preventing further automation and what it would take to improve it.