Teams with an AI idea but no PoC boundary
Teams that need to turn a promising AI topic into a measurable 90-day PoC instead of a broad innovation slogan.
AI PoC
AI PoC and R&D proposal planning
In-Stars reframes streetlight innovation, smart care, 3C3I, and energy cases into a reusable consulting method: challenge, approach, outcome, and the next PoC.
Submit an initial PoC request
Who This Is For
When an AI PoC must prove value before investment
If the topic is already important but the scope, evidence, owner, or budget decision is still unclear, In-Stars can help organize the first practical path.
Product, R&D, and field teams
Teams that must coordinate user scenario, data, prototype, validation site, and acceptance criteria.
Managers preparing budget approval
Decision makers who need evidence, risk, and expected outcomes before funding development.
Consultation Flow
From PoC idea to test boundary, evidence, and owner
In-Stars reframes streetlight innovation, smart care, 3C3I, and energy cases into a reusable consulting method: challenge, approach, outcome, and the next PoC.
Problem framing
Define the business problem, user, field constraint, and why AI is needed.
90-day PoC design
Define data scope, prototype scope, process owner, validation field, and acceptance metric.
Risk and feasibility review
Check data availability, integration limits, compliance, model risk, and operating preparation.
PoC decision package
Turn the PoC idea into a scope sheet, evidence checklist, validation criteria, and project note that management or partners can use to decide the next step.
Decision Prep
PoC validation and decision path
A PoC should begin with a clear explanation of what will be tested, what evidence will be collected, who will judge the result, and what decision follows.
Business problem and user scenario
Explain the pain point, current workaround, target user, and expected business impact.
Data and environment
Prepare sample data, device or system constraints, available APIs, and privacy limits.
Success metric and owner
Decide who owns the pilot and which metric proves it is worth continuing.
Outputs
A PoC decision brief before proposal writing
The first output is a decision package: what to do next, what evidence is missing, who should own it, and whether the topic is ready for a proposal, grant, training plan, or PoC.
PoC scope sheet
A bounded plan with the problem, target user, scope, owner, validation field, and success criteria.
Data and evidence checklist
A practical checklist of sample data, system limits, integration points, privacy constraints, and evidence to collect during the pilot.
Decision-ready project note
A partner or internal approval note with milestones, roles, validation criteria, risk notes, and the next decision point.
Timeline And Boundaries
How to keep the first PoC narrow enough to verify
PoC feasibility conversation
Decide whether the topic is ready for a PoC or still needs training and data cleanup.
PoC decision package
Prepare the scope sheet, evidence checklist, validation criteria, risk notes, and decision-owner alignment.
Focused pilot plan
A typical PoC should test one focused problem, collect evidence, and support a clear continue-or-stop decision.
Consultation Prep
What to prepare before an AI PoC proposal call
Bring one business problem, one user scenario, available data, known constraints, and the success metric that would justify the next investment.
Business problem and user scenario
Explain the pain point, current workaround, target user, and expected business impact.
Data and environment
Prepare sample data, device or system constraints, available APIs, and privacy limits.
Success metric and owner
Decide who owns the pilot and which metric proves it is worth continuing.
Turn the topic into an actionable next step
Share the current business topic and expected outcome. In-Stars will help choose the right next step across AI consulting, grant assessment, industry-academia collaboration, Japan DX (Digital Transformation), or PoC planning.