Build with AI
Proof of Concept
A package for companies that already selected a use case and need to prove on real data and in a specific workflow that the solution works technically and commercially before wider deployment.
What the package includes
Validating one use case in conditions close to real operations
Pricing grows when production-like data, stronger security requirements, broader stakeholder coordination, or integrations are involved.
- Work on a concrete use case using real data or a realistic sample.
- Technical and process validation in the target workflow.
- A pilot or PoC that can be assessed against agreed metrics.
- Measurement of impact, limits, and operational risks.
- A recommendation for production rollout, scope adjustment, or stopping the direction.
When it makes sense
A fit when you need proof, not just a proposed direction
- You already selected the use case and need to validate its value on your own data.
- You want to reduce the risk of a larger AI or automation investment.
- You need to show business and operational impact before a broader rollout.
- You are dealing with an internal tool, documents, reporting, or automation where measured value matters.
What the client gets
Outputs you can use to decide on production deployment
- A working PoC or pilot within the agreed scope.
- An evaluation of results against agreed metrics and goals.
- A view of constraints, risks, and gaps to solve before production.
- A recommended next phase with a practical implementation path.
- A basis for deciding whether to continue with Full Team or wider enterprise delivery.
What can follow
A PoC should create evidence for the next investment decision
If impact is confirmed, the PoC transitions into production delivery, integrations, and longer-term operations. If not, you still get a grounded basis to stop the direction without overspending.