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AI Infrastructure

Multi-Agent AI Operations Platform

A continuously-running AI operations platform where specialist agents do the repetitive work, and the human team focuses on judgement.

Azure AIClaude SDKPower BIPython
AI Infrastructure illustration

The challenge

The operations team was drowning in repetitive monitoring, reconciliation and reporting tasks — and the specialists who should have been doing higher-value work were the ones getting pulled in to firefight.

Our approach

How we structured the work, end to end.

01
Mapped the operational workflow end-to-end to find which tasks were rule-based and which genuinely needed human judgement.
02
Designed a multi-agent topology — specialist agents for monitoring, reconciliation, classification and reporting — orchestrated against a shared knowledge graph.
03
Built the runtime on Azure AI with custom agents calling internal services, and wired every action into Power BI for traceability.
04
Deployed scheduled and event-triggered jobs so the platform runs continuously without manual orchestration.

The architecture

From source to insight, in one governed flow.

01
Source Signals
02
Multi-Agent Orchestration
03
Knowledge Graph
04
Power BI / Scheduled Jobs

Outcome

What changed
Specialists got their time back. Routine monitoring, reconciliation and reporting now happen on autopilot, with humans only stepping in on exceptions.

Related work

Other engagements with a similar shape.

Process × Intelligence

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