IT & Cybersecurity1000+ (Upper mid-market)Cross-industry

AIOps: proactive incident detection & resolution

Correlate IT alerts, predict incidents, and automate first-line resolutions.

ROI ★★★☆☆Complexity ●●●○○6-12 months1000+ (Upper mid-market)

The problem

No reliable steering on aIOps: proactive incident detection & resolution.

The current process is manual or inconsistent.

Decisions come too late due to weak signals.

Operational and cyber risk is underestimated.

Prerequisites: required data & tools

Required data

  • Logs applicatifs
  • monitoring infra
  • ITSM

Compatible tools

  • Datadog
  • Dynatrace
  • BigPanda
  • PagerDuty + ML

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What we implement in 6-12 months

In 6-12 months: Correlate IT alerts, predict incidents, and automate first-line resolutions. with measured impact on MTTR reduction.

Weeks 1-2

Diagnosis

Weeks 3-6

Build

Week 7+

Delivery

Concrete deliverables

Business framing and decision rules for aIOps: proactive incident detection & resolution

Operational engine for aIOps: proactive incident detection & resolution

Steering dashboard with alerts

Action playbook and governance

Expert insight

Reduces MTTR by 30–60%. Relevant for mid-market firms with complex environments.

— Datasive, expertise terrain

Tech maturity

High

Mature solutions, fast deployment

Medium

Maturing tech, requires customization

Emerging

Cutting-edge innovation, R&D approach

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