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Agentic AI for IT & IT Services

AiXpertz.ai builds autonomous AI agents for IT operations teams — detecting and resolving incidents before users notice, correlating thousands of alerts into a handful of actionable events, automating DevOps pipelines end-to-end, and handling ITSM ticket triage around the clock.

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What We Automate

High-impact IT & IT Services workflows

AIOps Incident Detection

Ingests metrics, logs and traces; correlates signals across services; surfaces root-cause hypotheses before the pager fires.

60–80% less alert noise

Autonomous Incident Resolution

RAG-driven root-cause analysis over runbooks, executes approved remediation, escalates when blast-radius is exceeded.

50%+ faster MTTR

DevOps & CI/CD Automation

Monitors pipeline health, auto-triggers rollbacks on failed deployments, opens remediation PRs.

40–60% fewer failed deploys

Intelligent Monitoring

Learns normal service baselines, dynamically adjusts thresholds to suppress false positives.

Near-zero missed SLA breaches

Change & Config Management

Audits configuration drift against desired state, flags unauthorized changes, auto-remediates low-risk drift.

80%+ drift caught in minutes

ITSM Ticket Triage

Classifies inbound tickets, routes with context pre-attached, auto-resolves known L1 issues.

50–65% resolved autonomously
How It Works

A five-stage pipeline from telemetry to closed ticket

01

Ingest logs, metrics & traces

The agent normalizes the full observability stack into a unified event stream.

02

Anomaly detection & correlation

ML-based detection clusters related alerts, suppressing the noise that buries the real signal.

03

RAG root-cause analysis

Retrieval over runbooks and past incidents identifies the likely cause and approved remediation.

04

Autonomous remediation within guardrails

Approved actions execute automatically; anything exceeding blast-radius routes to the on-call SRE.

05

Post-incident report

A structured report and ServiceNow update close the loop automatically.

Why AiXpertz

Built for IT & IT Services, not generic AI

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Native toolchain integration

Pre-built MCP adapters for ServiceNow, Datadog, PagerDuty, Splunk, Kubernetes and GitHub Actions.

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ML-driven noise reduction

Graph-based alert correlation targets 60–80% noise reduction vs. static threshold rules.

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Mandatory approval gates

Any remediation exceeding the configured blast-radius threshold requires explicit SRE approval.

Ready to bring autonomous AIOps to your IT estate?

Every engagement begins with a risk-assessed pilot. If we don't deliver measurable results within the agreed pilot period, you pay nothing for the pilot phase.