AI prototype

Starting Point

A solution concept is in place. The assumptions are plausible. But assumptions are not facts. Does the model work with real data? Does the user understand what the prototype does? Is the latency acceptable?

Without a prototype, the project moves directly into an MVP – and teams often only realize then that the assumptions were wrong. A failed MVP costs weeks. A failed prototype costs days.

The AI prototype incorporates this validation stage. Functional in 2 to 6 weeks, with real data and initial test users. In the end: a well-founded go/no-go decision for the MVP.

What You Get

• 2 to 6 Weeks of Prototype Development - fast, focused on validating core assumptions.
• Functional Prototype with real data - not a mock-up, but real behavior.
• Initial User Tests with a structured test protocol and evaluation.
• Validation Report - what works, what doesn't.
• Performance Measurement - Latency, Output Quality, Token Consumption, Cost Projection.
• Go/No-Go Recommendation for the MVP decision.
• Handover Documentation ready for MVP development.

Approach

1. Setup - 2 to 5 days. Validation assumptions, user test setup, data access.
2. Build - 2 to 5 weeks. Iterative prototype build with short demo cycles, integrated user tests.
3. Handover - 2 to 5 days. Validation report, performance measurement, go/no-go recommendation.

Who it's for

Companies with a validated solution concept looking to minimize risks before making an MVP decision.
Innovation Managers and CTOs who need quick validation instead of lengthy discussions.
Departments that want to make a use case tangible for stakeholder buy-in.
Teams after a solution discovery.

Who it's not for

Companies without a clear solution concept - first solution discovery, then prototype.
Teams expecting production-ready output - a prototype is for validation, not delivery.
Use cases without data or user access.