Cloud & Platforms
A platform is not judged on the day it goes live but three years later: on what it costs, what it holds, and whether you could still leave it. Adservio builds the ones you can defend on those three counts.
A platform is judged three years after go-live.
Migrating is the easy part. What follows is harder: the bill that drifts as AI workloads arrive, the residency rule nobody wrote down, the dependency discovered the day you want to leave.
We treat those three from the design stage rather than at the audit. What a platform costs, where its data sits, and what it would take to move it are decisions, and decisions are written down.
What we do
Each step is a capability of its own, with its own page. They read in order, but a programme starts wherever the gap costs the most.
Application modernisation
Map the estate, measure the debt, score each batch by business value and technical complexity, then rebuild in batches rather than in one go.
See the capabilityCloud strategy & migration
Framing, secure landing zones, migration waves and a cutover that does not interrupt service. What moves is decided by value, not by ease.
See the capabilitySovereign & hybrid cloud
Data residency decided at design time, private, hybrid or qualified cloud, and the routing rule written into the infrastructure itself.
See the capabilitySecurity & resilience
Zero Trust, tested continuity plans and structured crisis management, aligned with the frameworks that apply to you: NIS2 and DORA.
See the capabilitySRE & observability
SLOs that are held rather than published, end-to-end observability, AIOps on root cause analysis and an incident response that is rehearsed.
See the capabilityFinOps & GreenOps
Cost and footprint tracked continuously, AI workloads included, where token billing and bursty inference break classic forecasting.
See the capabilityReversibility & portability
Being able to change host or bring workloads home, proven by an actual replayed switch rather than promised by a contract clause.
See the capabilityWhat you get at every step
Three principles hold across the whole chain, whichever step you enter at. Each is shown by a project that runs rather than stated: what gets executed, in order, and what the execution returns at the end.
The infrastructure is described, not configured
Zones, rights, retention and residency live in versioned files. A change can be reviewed, replayed and rolled back, and an environment is rebuilt from scratch rather than repaired from memory.
- What is not in the file does not exist
- A drift is read before it is applied
- Two environments are compared, not assumed
Both environments match the same description. A fix applied by hand on one of them would have surfaced at step two.
What shifted in 2026
Partners
We don't sell licences. The building blocks are chosen for your constraints, never the other way around, and integrated to the same engineering standard whatever the brand.
See the full ecosystemEuropean infrastructure and private cloud, chosen when data residency weighs in the architecture decision rather than after it.
Sovereign hosting in France when the workload must not leave the territory, on the same foundation and the same deployment chain as the rest.
Metrics, logs and traces gathered in one place, so an incident is investigated from a single thread rather than from four consoles.
Observability on the platforms and the applications: what goes live keeps being measured, from the trace down to the cost.
Platforms in production
A deployment chain that replays itself, on Azure
230 industrialised pipelines · 0 critical vulnerability
Deployments and data flows handled without a shared chain: every change replayed by hand, and nothing guaranteeing that two environments behaved the same way.
A DevOps and DataOps chain built on Azure: environments described as code, pipelines industrialised, security checks wired into the chain rather than run at the end. A deployment becomes an execution instead of an operation.
An exchange architecture that outlives the applications on it
÷4 time-to-market · 240 vehicles tracked
Systems that had to exchange in real time across a European cold chain, where each new connection was rebuilt from scratch and every addition slowed the next one down.
An interoperable BUS architecture rather than point-to-point links, a platform delivered through Design Thinking with the business, and a delivery chain that shortened time-to-market instead of the scope.
Critical applications kept in service, workshop after workshop
0 regression · over 90% test coverage
Supervision applications used daily in rail maintenance workshops, where a regression does not fill a backlog but stops a train from being released.
A coverage produced at the same pace as the code, and a rollout workshop by workshop rather than in one go. Each site is validated on its own before the next, so a gap is caught where it appears.
Insights & Perspectives
Cloud Native: building for the Kubernetes era
Cloud native has become a buzzword. What it actually means is architecting applications to use what a modern platform offers, rather than deploying the same thing somewhere else.
Platform engineering: scaling DevOps across the hybrid cloud
A dedicated platform team, hybrid cloud architecture, developer portal, IaC and AI agents: how platform engineering scales DevOps across hybrid environments.
AI and IT resilience
How AI shifts IT resilience from reactive to anticipatory: pattern recognition, automation, threat detection, observability, and the limits of full automation.
The other foundations
ExpertiseData for AI
The data foundation on top of the platform: quality, governance, lineage and the pipelines that feed your models.
ExpertiseGenAI platforms
A sovereign, governed GenAI foundation: hybrid LLM gateway, RAG platform, LLMOps and AI FinOps.
Build a platform you could still leave
A mapping of the estate, a costed trajectory, and the three decisions written down: cost, residency, exit.
Frequently asked questions
Because AI workloads do not behave like the infrastructure FinOps was built for. Token billing and bursty inference make forecasting structurally harder, and wasted spend went back up to 29% in 2026 after five years of decline.
No, it is an arbitration. More than half of companies plan to move some workloads back, mainly for unexpected cost and then for compliance. What matters is not the direction but whether the move is possible at all, which is decided long before it is wanted.
That the data and the processing stay under a jurisdiction you chose, and that no foreign law can reach them. In France the SecNumCloud qualification attests to it. It is a decision about where each dataset sits, not a label applied to a whole platform.
By replaying it. A clause that has never been exercised tells you nothing about the managed services, proprietary formats and identity dependencies you would have to unwind. Reversibility is proven by an actual switch on a real scope.
Moving an application unchanged buys time and rarely value: the same defects run somewhere more expensive. Modernising everything first delays the benefit. The arbitration is made per batch, on business value and technical complexity, not for the estate as a whole.
Yes, provided the service levels are written and measured. What breaks a platform is not the absence of a team but the absence of an agreed objective: without an SLO, every incident is arbitrated in the moment and nothing is learned from the last one.
With the mapping, because it is what turns opinions into arbitrations: dependencies, obsolescence, coupling and the cost of each batch. It takes weeks, not months, and it is what makes the rest of the trajectory negotiable rather than declared.