Target Operating Design
The target design for the undertaking—objective, ownership, AI and human roles, systems, exceptions, outcomes, and completion conditions. A shared operating reference for business and technical owners.
Start with Work that matters.Design it for production.
A consequential process needs more than a capable model. The Governed AI Review produces a production design for one real undertaking: where AI should participate, which evidence counts, who can decide and act, and what establishes a successful outcome.
What you leave with
Four deliverables you can use independently—or carry into an Indwel implementation without starting the design again.
Value Case
The current operating baseline, where the data supports it, and the measures AI should improve—volume, handling time, expert hours, rework, exceptions, cost of delay, service levels, or throughput.
Evidence & Control Design
The evidence the Work may rely on, the standards that govern it, who may decide, what AI and tools may do, and the requirements for approval, exceptions, observation, and completion.
Production Plan
Integrations, dependencies, deployment assumptions, organizational decisions, acceptance criteria, and implementation sequence.
What the Review answers
The Work may be structured, judgment-heavy, exception-rich, long-running, or spread across people and systems.
What outcome are we improving?
We define the objective, accountable owner, scope, and conditions that constitute success.
Where should AI do the work?
We identify where inference creates leverage, what remains deterministic, and where human judgment still matters.
What information can we rely on?
We identify the Evidence the Work may rely on and, separately, the policies and standards that govern how it is judged.
Who decides, approves, and acts?
We make decision rights, escalation, approvals, permissions, and action boundaries explicit.
How will we know it worked?
We define observable outcomes, exception handling, and the conditions that establish completion.
What has to happen next?
We identify dependencies, controls, acceptance criteria, value assumptions, and decisions that remain open.
A capable model can still produce the wrong outcome.
Dependable Work also requires the right evidence, decision rights, action boundaries, exception handling, and completion conditions.
An accessible source may still be the wrong Evidence for this decision.
A valid recommendation may reach someone without authority to approve the action.
An API may report success while the intended business outcome never occurs.
The Review tests those gaps before the organization depends on them.What happens during the Review
We work with the people who own the outcome and understand the systems, policies, and operating constraints around it.
Current reality
Representative cases, systems, controls, exceptions, pain points, and the operating baseline.
Target design
Where inference creates leverage, what remains human or deterministic, what evidence and authority are required, what may act, and what completion requires.
Test the design.
We test the target design with the responsible owners, resolve what can be resolved, record what remains open, and prepare the final outputs.
The engagement
What we need from your teamThe owner and the people who know the Work
A business owner, representative cases or artifacts, and access to the people who understand the relevant systems, policies, risk, and operations.
Closing reviewResponsible owners leave knowing what is established and what remains open
We walk the final outputs together, confirm what has been established, and make remaining dependencies and open decisions explicit.
Commercial terms$12,000 fixed
One process and four deliverables, with scope and inputs agreed before kickoff. No software purchase is required.
If you proceed with IndwelWe do not start over
The operating design, evidence and control requirements, integration decisions, acceptance criteria, and success measures carry directly into implementation.
Bring the Work you are ready to improve.
Start with one consequential undertaking. Leave knowing how it should operate, what value AI should create, what must remain under your control, and what happens next.