AI Retainer Model
A commercial structure in which a business pays a monthly fee for committed AI engineering capacity over a 12-month minimum term, rather than paying per-project or per-seat.
How it works
Production AI infrastructure is not a one-off build. The first workflow proves the value, the second and third compound on top, models move forward, integrations drift as upstream systems change, compliance regimes tighten, and new automation opportunities keep surfacing. A project-by-project commercial structure does not fit that shape. A retainer does. Ayoob AI operates two retainer entry points: an existing systems retainer for businesses with AI already running that needs proper engineering ownership, and a new systems retainer for greenfield builds. Both run on a 12-month minimum term and scale with scope. Hosting and model API costs sit outside the retainer and are paid by the client to their own providers.
Related terms
Full Code AI Automation
AI automation built as custom software the client owns: code in the client's repository, deployment in the client's infrastructure, integrations against real APIs, with no per-seat licences and no third-party canvas in the data path.
Custom AI Software
AI capability delivered as bespoke software tailored to a specific business's systems, workflows, regulatory context, and integration requirements, rather than a generic SaaS product.
Build vs Buy AI
The commercial decision between commissioning custom AI software (build) and licensing an off-the-shelf AI product (buy), with the right answer depending on workflow specificity, regulatory constraints, integration depth, and total cost of ownership.
Want to see this technology in action?