01
Ritual 1
Regular review of indicators
A joint reading of the indicators defined at deployment. What's holding, what's slipping, what deserves an adjustment. Not a dashboard you look at once and forget.
Continuous Optimisation
Keep your AI solutions alive over time.
Regular support after deployment: indicator tracking, adjustments, technology watch, availability. So the solutions you've put in place stay useful, relevant and maintained, without it becoming an internal burden.
The observation
Deployment isn't the end. It's the start of real use.
An AI delivered and forgotten loses its relevance. Uses evolve, so does data, models change. Without continuous steering, a solution that worked well ends up producing mediocre results, and no one knows why.
Continuous optimisation means keeping a hand on what has been put in place. Watching the indicators, adjusting when needed, integrating what deserves it, without relaunching a project each time.
That's what turns a one-off success into a lasting advantage.
The rituals
Four rituals, a mechanism that holds.
Regular, structured touchpoints, calibrated to your pace, without overload or formal meetings for their own sake.
02
Ritual 2
Operational adjustments
Targeted improvements: prompt optimisation, knowledge-base updates, threshold calibration. AI solutions drift; they need re-framing.
03
Ritual 3
Applied technology watch
The AI ecosystem moves fast. I filter the noise to bring you only what can concretely improve what you have in production.
04
Ritual 4
Availability
A direct channel for your operational questions. No ticket to open, no support tier to climb. A quick answer when something goes wrong.
Deliverables
What you receive.
Periodic report
A regular summary of the state of the deployed solutions, the adjustments made, the points to watch. Legible, short, actionable.
Documented adjustments
Every change is logged: what changed, why, what effect was observed. No mysterious evolution, no silent debt.
Evolution recommendations
When a new use or a new technology deserves a project of its own, I flag it to you clearly rather than slipping it in quietly.
Knowledge continuity
The documentation stays up to date. Your team can always take back control if you decide to end the support.
What you gain
Continuity with no hidden burden.
Solutions that stay useful
An AI deployed and abandoned loses its value within months. Regular support keeps the solutions at the level they were designed for.
A predictable cost
A regular engagement framework smooths the effort and avoids costly emergencies. Predictability is a deliverable too.
A long-term partnership
You keep on hand someone who knows your context. No need to re-explain with every request.
Preserved freedom
The support is designed to make you more self-reliant, not more dependent. At any moment, you can decide to continue, adjust or stop.
Frequently asked questions
What I'm asked most often.
Do I need to have gone through an implementation project with you?
No. The support can also cover AI solutions deployed by other teams or providers, provided the existing documentation allows an effective handover.
How often are the exchanges?
Adapted to your context: regular reviews for stable solutions, closer contact during adjustment phases. The pace is calibrated together from the start.
Can the engagement be ended at any time?
Yes. The support only makes sense as long as it brings value. No imposed minimum-term commitment.
And if a new project emerges?
A new project falls outside the scope of the support and is discussed separately. It's clear for everyone, and it avoids scope creep.
Ready to think long term?
Book a discovery call. We assess together whether a regular support framework matches what you need right now. No commitment.