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AI StrategyAgentic AIEnterprise Operations

AI-Powered Operations for a Global Technology Enterprise

Building an Agentic AI incident triage system and RAG-powered knowledge assistant that transformed enterprise operations from reactive firefighting to intelligent automation.

90%
AI Triage Accuracy
93%
Knowledge Retrieval Accuracy
<5s
Incident Response Time
100%
Retrieval Precision
22
Automated Test Cases
2
AI Systems Delivered

The Challenge

Manual Operations at Enterprise Scale

A global technology enterprise was struggling with incident management at scale. Their operations team was drowning in alerts -- hundreds of incidents daily across distributed infrastructure, each requiring manual classification, routing, and response. Average time to triage an incident exceeded 45 minutes, with critical issues sometimes waiting hours before reaching the right team.

Compounding the problem, institutional knowledge was scattered across wikis, runbooks, Confluence pages, and the minds of senior engineers. When those engineers were unavailable, the team was left searching through dozens of documents to find the right troubleshooting steps -- often under pressure during active incidents.

The client needed two things: an intelligent system that could automatically triage and respond to incidents at machine speed, and a knowledge assistant that could instantly surface the right information from their documentation -- with citations, not guesswork.

Solution 1

Agentic AI Incident Triage System

An event-driven architecture where AI decides and workflow executes -- with built-in safety guardrails and full audit trails.

1

Event Ingestion

Incidents are ingested in real-time through Azure Event Hub using AMQP over WebSocket. A producer-consumer pattern ensures reliable, ordered delivery of events regardless of source -- monitoring tools, ticketing systems, or manual triggers.

2

AI-Powered Triage

The Agent Service, powered by GPT-4.1 on Azure OpenAI, analyzes each incident. It classifies severity, identifies root cause patterns, determines the appropriate response action, and outputs a structured JSON decision with confidence scores.

3

Policy Engine

Every AI decision passes through a policy engine. Safe actions (low-risk, high-confidence) auto-execute immediately. Risky actions (production changes, escalations) are queued for human approval -- ensuring AI augments, never overrides.

4

Automated Execution

The Workflow Service executes approved actions through specialized executors: ticket creation, team notifications, remediation scripts, and escalation workflows. Every action is fully audited with timestamps and decision trails.

Architecture Pattern

Producer → Event Hub → Consumer → AI Agent (GPT-4.1) → Policy Engine → Workflow Service → Actions + Audit

Safe actions auto-execute. Risky actions require human approval. Every decision is logged.

Solution 2

RAG-Powered Knowledge Assistant

An AI assistant that provides instant, accurate answers from internal documentation -- with inline citations and zero hallucination.

1

Document Ingestion

Internal documentation, runbooks, architecture docs, and knowledge base articles are ingested, chunked, and embedded using OpenAI text-embedding-3-small. Vectors are stored in ChromaDB for fast, semantic retrieval.

2

Semantic Query

When a user asks a question, the system performs semantic search across the vector store with a tuned relevance threshold (0.35 minimum), retrieving the most contextually relevant document chunks.

3

AI-Generated Answer

GPT-4.1 generates a comprehensive answer grounded in retrieved documents. Every response includes inline citations pointing to the exact source -- no hallucination, full traceability.

4

Conversation Memory

The assistant maintains conversation context across interactions, enabling follow-up questions and multi-turn dialogue. Streaming responses ensure a fast, interactive user experience.

15/15
Retrieval Accuracy

Every query found the right context

14/15
Faithfulness Score

Answers grounded in source documents

14/15
Citation Accuracy

Correct source attribution in responses

Technology Stack

Built with Modern AI & Cloud-Native Tools

Azure OpenAI (GPT-4.1)Azure Event HubPythonFastAPIChromaDBLangChaintext-embedding-3-smallPydanticasyncioGitHub ActionspytestruffDockerRAG ArchitectureAgentic AIPrompt Engineering

Outcomes

Key Results Delivered

Incident triage time reduced from 45+ minutes to under 5 seconds
90% AI triage accuracy validated through rigorous evaluation pipeline
93% overall knowledge retrieval accuracy (retrieval + faithfulness + citation)
100% retrieval precision -- every query found the right context
Agentic safety guardrails: risky actions require human approval before execution
Full audit trail for every AI decision -- complete traceability and compliance
22 automated tests with CI pipeline: lint, unit tests, and AI evaluation
Streaming responses for real-time, interactive knowledge assistant experience
Conversation memory enables multi-turn dialogue for complex troubleshooting
Scalable event-driven architecture handles high-volume incident streams

Ready to Bring AI to Your Operations?

From agentic AI systems to RAG-powered knowledge assistants -- let's explore how AI can transform your enterprise operations.

Book a Free Consultation