Proof of value
Prove AI can create value in the physical value chain.
In 2-3 months, we help operations teams understand the right AI opportunities, scope the workflows that matter, and execute pilot-scale production work across engineer, plan, source, make, and deliver.
2-3 months
Timeboxed production proof
2-3 workflows
Scoped around real value
5 stages
Engineer -> plan -> source -> make -> deliver
What we prove
Not whether AI is interesting. Whether it changes the work.
A useful proof of value is close enough to production that the result can be trusted. We do not stop at discovery, prompts, or a sandbox demo. We put myai against a real workflow, with real users, real systems, and a business reason to keep going.
The proof is the evidence: less manual chasing, clearer decisions, better handoffs, preserved expertise, or a workflow that reaches a measurable operating KPI.
How it works
Understand. Scope. Execute.
Understand
We map the places where expert judgment, system gaps, and manual work are slowing the business down. The output is a ranked view of relevant AI opportunities, not a generic list of demos.
- Interview the people closest to the work
- Trace the systems, spreadsheets, inboxes, and decisions involved
- Separate interesting AI ideas from meaningful operational problems
Scope
We narrow the work to the use cases that can prove value quickly. Each candidate gets a clear business owner, value hypothesis, data path, workflow boundary, and definition of done.
- Choose the workflows most tied to margin, throughput, quality, or working capital
- Define the production path for 2-3 use cases
- Agree on what evidence will prove the pilot worked
Execute
We build with your team inside myai and put the pilot into real operational use. The work is pilot-scale, but it runs in production against the core part of the value chain that makes money.
- Connect the systems and artifacts the workflow already depends on
- Ship working agents, workflows, canvases, and traceable outputs
- Measure whether the work creates enough value to expand
Where it lands
Focused on the chain that makes money.
The proof of value starts where operational decisions turn into margin, throughput, cash, quality, or customer commitments.
01
Engineer
Part metadata, change requests, design intent, and tribal engineering knowledge.
02
Plan
Demand/supply balancing, scenario analysis, S&OP artifacts, and planning rationale.
03
Source
Supplier follow-up, shortage management, lead-time risk, and procurement exceptions.
04
Make
Production traceability, NCR management, quality reviews, and root cause analysis.
05
Deliver
Fulfillment handoffs, customer commitments, status visibility, and cross-system follow-through.
What you get
A working proof, plus the decision packet behind it.
The output is not just software and not just a report. It is a production-scale proof with enough evidence to decide whether to expand.
Why this is controlled
Production enough to matter. Bounded enough to manage.
Bounded scope
The proof of value is narrow enough to ship, but close enough to production that the result means something.
Real users
We work with the operators, planners, engineers, and managers who already own the workflow.
Production evidence
The goal is not a sandbox demo. The goal is evidence that a workflow can create value in the business.
Governed rollout
Access, traceability, and human review stay visible so the pilot can survive IT and leadership scrutiny.
The bar is proof, not activity.
At the end of the engagement, the question is simple: did the work create enough operational value to justify the next step? If yes, we know where to expand. If not, the proof did its job and prevented a bigger bet on the wrong thing.
Bring us the mess.
We’ll show you the map.
Every conversation starts with your problem, not our pitch. Book 30 minutes and we’ll explore whether myai fits.