AI design sprint for manufacturing

Rank AI use cases in quality, maintenance and planning, check your data, and get a costed Go/Pivot/Kill verdict.

Itransition's AI sprint helps you decide which AI ideas deserve investment before you commit to a full build, using your own data and volumes.

We score candidate ideas from four areas of production (quality, maintenance, planning and operator support) against feasibility and ROI.

Our approach is to:

1. Rank your use cases: score candidate AI ideas on feasibility and ROI

2. Audit your real data: grade the readiness (DRL 1-5) of the sensor, MES/ERP, QMS and historian data behind your top-ranked use case

3. Test model feasibility: define an AI Logic Contract for exactly what the model would read, check and decide, then stress-test it against your data

4. Build the business case: quantify time saved, errors reduced and cost avoided, then issue a Go / Pivot / Kill verdict

Your involvement includes:

- Candidate AI ideas across your workflows

- Data files supporting those workflows

- Your team's time and expertise

What you receive is four deliverables built to carry your next planning cycle, not just this sprint:

- AI job description: a written spec of what the AI will read, check, draft and answer

- Data readiness verdict: a graded assessment with the fixes needed before go-live

- Quantified business case: calculated from your own volumes and validated with your team

- Deployment plan: scoped requirements and test scenarios for a beta build in your own cloud

Share your production AI use cases and we'll tell you which one is worth testing.