The nature of model-based solutions
A solution built on an AI model operates in a dynamic environment. Providers update their models regularly, and as the organisation grows, its data and the way the people using the solution work change as well.
Maintenance therefore includes continuous monitoring of quality, cost and performance, and deliberate management of every change. The solution keeps performing to a high standard and evolves together with the technology.
Evaluating new models
Each new generation of models offers higher quality, lower cost or new capabilities. We assess every new model against the organisation’s specific use cases, on test sets built from real cases of the process in question. We compare:
- quality and accuracy of results,
- stability in typical and complex cases,
- processing cost,
- response time,
- compliance with security and data residency requirements.
We recommend changing a model when the evaluation confirms a technological or economic benefit. We introduce the change through change management, with testing and the option to roll back.
Every new generation of models is an opportunity for a better result. Systematic evaluation allows the organisation to take full advantage of it.
Scope of maintenance
- Monitoring — availability, quality of results, performance and cost of the solution.
- Model evaluation and updates — assessment of new versions on real cases and structured rollout of changes.
- Management of provider-side changes — early assessment of the impact of updates, planned model retirements, pricing and processing terms.
- Functional development — the solution grows with the organisation’s needs.
- Compliance review — the register, risk classification and human oversight remain up to date.
Where the organisation has its own AI environment, maintenance covers it as well: performance, costs, the model lifecycle and development of the company knowledge layer.
Service levels
Maintenance runs on a subscription model with clearly defined service levels: a specified scope, response time and an incident reporting and escalation path. Every solution is entered in the organisation’s service catalogue, so in the event of an incident it is clear who restores service, within what time and who makes the decisions.
This is the IT service management discipline we have applied for years to business-critical systems in large organisations, now brought to AI solutions.
Complete documentation
Documentation and operating instructions are created during implementation. We document every solution so that the organisation’s team can take it over in full.
The organisation retains full knowledge of its solutions and full independence in its decisions. Our maintenance partnership continues on the strength of the value it delivers.
Evolving with the technology
Maintenance also includes development. As new tools and ways of building solutions emerge, we identify those that bring value to the organisation and propose changes backed by a technological and economic rationale.
The periodic review provides a broader view of the direction of the organisation’s entire ecosystem.