AI strategy and delivery

A software company comes here with one of three problems: an AI idea that still needs a decision, one feature that has to reach production, or coding agents each developer has set up alone. The work below takes different shapes. Buying one piece does not commit you to the others.

The Full AI audit is for a team that has not chosen yet. Over one to two weeks we name the feature and what good enough means, then leave a written decision: build, fine-tune, or stop. Build points to a later production sprint. Fine-tune points to a private model, and only if an evaluation shows the hosted model falls short. Stop means we do not start a build. The audit ends at the decision. It does not ship a system.

The AI production sprint is for a company that already knows which feature should go live. In four to six weeks we put one search-and-answer system or one agent into production, with evaluations, monitoring and a runbook. It is one system. Afterwards you run it, or Managed AI operations looks after it on a separate monthly agreement. The sprint does not choose build or stop, and it does not tune a model.

The AI coding rollout is for the engineering team, not for a feature customers use. For one repository we leave a shared setup for coding agents: context files, agent skills, security boundaries, continuous integration and evaluation gates, and training. You own the files. Another repository is a later order.

Use them in order only when you want that path: a decision, then one system in production, then care of what is live. Many companies take a single piece of work. Contact us for pricing. Each one is a fixed price, agreed before we start.