FROM AN IDEA TO ACCEPTED WORK

Start with the work.
Build the right AI around it.

A practical path to local AI for your business. Validate one workflow before committing to a broader rollout.

Define the outcome

Choose a business loop, monthly volume, reviewers, and the systems involved. Decide what a useful result looks like.

Output / a scoped pilot brief

Fit the infrastructure

Assess existing hardware first. Compare model memory, concurrency, software compatibility, and operating costs before proposing a new machine.

Output / a hardware and runtime shortlist

Evaluate the model

Start with prompting and retrieval. Consider fine-tuning only when representative evaluation shows a worthwhile improvement. Confirm model licensing for the intended use.

Output / a measured baseline and model recommendation

Build in a sandbox

Use synthetic or approved records. Connect only the tools the workflow needs and define approval checkpoints.

Output / a reproducible pilot and review queue

Measure, then decide

Compare accepted-task cost, quality, review time, and payback with your current process. Scale only when the evidence supports it.

Output / an acceptance report and deployment decision