How Madhi Works

From the first problem to production ownership, this is how we discover, validate, build, deploy, evaluate, and transfer dependable AI systems.

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Ownership

The end client owns the intellectual property developed specifically for their project.

This includes source code, prompts, evaluation datasets and frameworks, configurations, project-specific training data, documentation, and infrastructure developed as part of the engagement.

Where models are trained, fine-tuned, or adapted specifically for the client, ownership and usage rights are defined as part of the engagement. Third-party and open-source components remain subject to their licences and are documented accordingly.

Where practical, repositories, infrastructure, model-provider accounts, and operational tooling are established directly inside the client environment from the beginning.

The client also retains the evaluation framework. Models and providers may change, while the organisation’s definition of correct behaviour, important edge cases, known failures, and acceptable performance remains a durable asset.

Handover includes the documentation, runbooks, evaluations, and technical knowledge required for the team to operate and continue developing the system independently.

Let’s define the right next step

Share the outcome you need. We’ll help determine the right approach, what to validate first, and how to move toward production.