AIOps
Put AI to work on your operations data.
AIOps works when the foundations do. We build the observability, event pipelines and automation that let AI genuinely reduce alert noise, speed up diagnosis and assist incident response — instead of adding another dashboard.
- 01Telemetry & Events
- 02Correlation
- 03Anomaly Detection
- 04Incident Context
- 05AI-Assisted Diagnosis
- 06Remediation
The problem
What's actually going wrong.
Drowning in events
Monitoring produces thousands of events per incident and engineers correlate them by hand across tools.
Static thresholds, dynamic systems
Fixed alert thresholds miss real anomalies in seasonal, fast-changing workloads — and fire on normal ones.
Slow diagnosis
Finding the relevant change, deployment or dependency during an incident takes longer than fixing it.
AI without foundations
An AIOps tool was purchased, but fragmented telemetry and missing context make its output untrustworthy.
What we do
AIOps capabilities.
Event correlation
Grouping related alerts, changes and telemetry into a single incident view instead of a flood of pages.
Anomaly detection
Baselining and detection tuned to real workload patterns, complementing SLO-based alerting.
Alert noise reduction
Deduplication, suppression and routing rules that cut page volume without hiding real impact.
AI-assisted diagnosis
Surfacing likely causes, recent changes and relevant runbooks during an incident.
Automated remediation
Guarded automation for well-understood failure modes, with human approval where risk demands it.
Observability foundations
The telemetry quality, service catalog and change data every AIOps capability depends on.
Technical capabilities
Technologies and practices.
Examples of tools we work with. Listed as capabilities, not certifications or partnerships.
- OpenTelemetry
- Prometheus
- Grafana
- Loki
- Elasticsearch
- Kafka
- Kubernetes
- PagerDuty
- BigPanda
- Moogsoft
Outcomes
What changes.
Fewer, richer incidents
Correlated context replaces alert storms.
Faster diagnosis
Likely causes and recent changes surfaced automatically.
Trustworthy automation
Remediation that acts on well-understood failures, with guardrails.
How we engage
Assessment → Architecture → Implementation → Enablement.
- 01
Discover
Understand the architecture, constraints and engineering bottlenecks.
- 02
Architect
Define the target architecture and implementation roadmap.
- 03
Build
Implement infrastructure, automation, platforms and reliability improvements.
- 04
Enable
Transfer knowledge and create sustainable engineering practices.
FAQ
Common questions.
Related insights
Further reading.
Related services
Often combined with.
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