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Maintenance in Trusted Condition

Maintaining mastery, beyond availability.

RUN, security, quality and compliance piloted with explicit criteria and readable governance.

Our conviction

Maintaining is not enough

Silence is not health

A system with no apparent incident can harbour unpatched CVEs, obsolete dependencies and invisible configuration debt.

Compliance drifts

AI Act, GDPR, NIS2 evolve continuously. A compliance snapshot ages fast without active review and a designated owner.

The team absorbs the shocks

Without structured supervision, your teams handle alerts instead of delivering value. RUN consumes BUILD.

The 4 axes of our MCC

Availability

Continuous monitoring, incident management, service continuity. Defined and measured SLAs.

Security

Continuous monitoring, patches, CVE management, progressive hardening.

Compliance

Traceability, AI Act, GDPR, NIS2. Audit-ready at any time.

Evolvability

Corrective and adaptive maintenance. The system improves, it does not stagnate.

From suffered RUN to mastered MCC

Availability, security, compliance: piloted with explicit criteria and readable governance.

BEFORE Common situation
  • Reactive maintenance We fix when it breaks, with no visibility or anticipation.
  • Fuzzy SLAs No measured objective, nor shared with the client.
  • Untracked incidents No post-mortem, the same problems keep coming back.
  • Security as catchup CVEs patched weeks, sometimes months, after publication.
AFTER With REELIANT
  • 24/7 supervision Real-time alerts, shared dashboards, anticipated incidents.
  • Measured & shared SLAs Co-defined objectives, transparent monthly reporting.
  • Proactive detection Incidents identified and resolved before user impact.
  • CVEs patched within 72h Continuous monitoring, patches tested and deployed quickly.

AI-specific

AI systems require dedicated MCC

Drift monitoring

Model performance tracked over time. Degradations detected before they impact users.

Update management

Impact control when models evolve. No silent regression after an update.

Production guardrails

Behavioral filter tracking and anomaly detection. Safeguards remain effective over time.

Continuous compliance

AI Act, GDPR, NIS2 ongoing, not annual snapshots. Audit-ready at any time.

What you gain

Increased reliability

Drifts are detected before they become incidents. Fewer late nights, fewer crises.

Reduced risk

Security and compliance handled continuously, not in a post-incident panic.

Operational clarity

You always know where your system stands. Clear governance for your business and IT teams.

Sustainability

Maintainable, documented systems, even if the team that built them changes.

Frequently asked questions

What is MCC (Managed Continuous Control)?

A managed services contract structured around 4 axes: availability (measured SLAs), security (patches, CVEs), compliance (GDPR, AI Act, NIS2 on an ongoing basis) and evolvability. Unlike traditional managed services, MCC includes ongoing compliance responsibility.

How do you monitor AI model drift in production?

Through an LLMOps framework that continuously measures response quality indicators, detects regressions after each model update and triggers alerts before drift impacts users.

How do you maintain GDPR, NIS2 and AI Act compliance over time?

Compliance is not a state, it's a process: regular reviews, decision traceability, up-to-date processing registers, planned internal audits. We designate a dedicated compliance lead, always ready for an inspection.

Is a system with no apparent incidents necessarily healthy?

No. Unpatched CVEs, obsolete dependencies or invisible configuration debt can coexist with a complete absence of incidents,until the day they don't. MCC supervision detects these silent drifts.

Ready to sustain your critical systems?

Whether you have a heavy technical legacy or new AI modules to secure, we can run an initial trust diagnostic.

Assess my system's trusted condition