Artificial Intelligence pricing
We publish starting prices so you can budget before the first call. Every quote is fixed-fee: no hourly surprises, no scope creep surcharges.
How we price projects
Every Build quote is fixed-fee. We scope the work during the Assess phase (or a shorter scoping call if you already have a clear brief) and give you a number that does not change unless you change the scope. Here is what drives that number.
Data complexity. A single clean CSV is simpler than five databases plus a legacy ERP export. The more sources we need to integrate and clean, the more engineering hours go in.
Model type. A tabular regression model costs less than a custom object-detection model that needs thousands of labelled images. If labelling is needed, we quote it separately or train your team to do it with our annotation tool.
Deployment environment. Deploying to a managed cloud service like AWS SageMaker or Google Vertex is straightforward. Deploying to on-premise servers or edge devices (Jetson, Coral) requires additional testing and packaging work.
Compliance requirements. If your industry requires model explainability documentation, bias audits or GDPR data-processing impact assessments, we include those as line items so you can see exactly what you are paying for.
We do not charge by the hour for project work. Hourly billing rewards slow work; fixed fees reward efficiency. The only hourly element is the 20-hour monthly allocation in the Managed AI plan, and unused hours do not roll over.