Proof of value

For organizations interested in verifying that an AI solution will deliver value. We help you assess if and how an AI model will work for your project.

What is a proof of value

A Proof of Value aims at exploring and validating if a client’s problem can be solved by using AI. It is highly similar to a Proof of Concept. However we go beyond the traditional feasibility check of a Proof of Concept by ensuring that the PoC also helps assess possible value generation for the company. The objectives of a Proof of Value are generally :

  • Validation: Testing how well an AI model can perform on a specific use case or dataset;

  • Data assessment: Testing if data is sufficient to tackle the problem - Understanding what data is needed;

  • Getting user feedback : gathering feedback from internal and/or external users. The users can be technical users or business users.

Benefits of a Proof of Value

  • Validation: Minimizing risk by testing feasibility of a specific solution;

  • Speed: Getting initial answers in a minimal time frame;

  • Cost: Committing minimal budgets;

  • Dependency: Testing if an AI solution or AI partner is the right choice;

  • People: Mapping who are the best collaborators to drive the project to success;

  • Decision : Ensuring our clients have internal buy-in on the next steps.

Deliverables of a Proof of Value

The deliverables of a Proof of Value will depend on the project scope. Here are 3 possible deliverables :

  • An AI model: An AI model that can solve a specific problem, on a specific dataset. This is a first, minimal AI model that can be extended when the AI solution is deployed.

  • A detailed report: A report on the findings of the proof of concept. We identify technical dependencies and share findings about the possible value generation if the model is to be deployed into production.

  • Operational recommendations: Recommendations on further steps to deploy a model into production.

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