Service

AI Proof of Concept

Fast, technically sound validation of a concrete AI use case – from data access to a runnable prototype with clear evaluation criteria.

  • Generative AI
  • Machine Learning
  • Computer Vision
  • Data Preparation
  • Evaluation

An AI proof of concept answers a question with facts: Does the use case work with the available data and models – and at what cost? The result is a runnable prototype plus reliable statements, not a demo shell.

Process

  1. Concretize the use case and define success criteria
  2. Review the data situation – quality, volume, accessibility
  3. Evaluate models and build the prototype
  4. Measure the results and give a production recommendation

Deliverables

  • Evaluated use case with a feasibility statement
  • Runnable prototype on real data
  • Clear evaluation criteria and measurements
  • Recommendation for production or stop

Pricing on request – depending on scope and architecture.

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