How we take agents from idea to production. Client names are withheld unless they have approved publication.
Selected work. Client names are withheld unless they have approved publication.
Challenge: Release status lived across thousands of Jira issues and several internal tools. Programme managers spent hours each week assembling status by hand.
Approach: A multi-agent system with planner, executor and display roles, connected to Jira and internal tools through MCP. Policy-as-code checks run before every action, and procedural memory lets the system reuse proven workflows.
AgentOps: A golden-dataset evaluation harness validates functional match, tool-call parameters and trajectory for every release, with profiling to manage latency and token cost.
Outcome: Release questions answered in natural language in minutes instead of hours of manual reporting.
Challenge: Each team wanted its own document assistant, risking duplicated effort and inconsistent security.
Approach: A single Kubernetes-hosted retrieval platform with shared ingestion, retrieval, caching, monitoring and chat UI, and multi-tenancy so each team gets an isolated assistant.
Outcome: New assistants launch from a common, governed base instead of being rebuilt each time.
Challenge: Recovery capabilities had grown unevenly across hundreds of applications and multiple data centres and clouds.
Approach: Enterprise DR strategy, application tiering, recovery targets and runbooks, delivered with the client’s infrastructure, cloud and architecture leaders.
Outcome: A clear, tiered recovery strategy and the runbook foundation for our DR Runbook Agent.
Challenge: Recruiters screened every resume manually against each role.
Approach: An Azure-hosted platform with a Power Apps front end that parses resumes and matches candidates to job descriptions, keeping recruiters in control of shortlists.
Outcome: Faster, more consistent first-round screening.
In a 30-minute call with a senior architect, you'll learn whether an agent can take it on, what it would cost to build and run, and how we'd prove it works.