Solutions · 06
Monitor, evaluate, govern, support, and improve AI systems after launch so they remain useful, controlled, and aligned with changing business needs.
AI does not become a stable business capability at deployment. Models, prompts, knowledge, workflows, costs, user behavior, and policies change. Without clear ownership, teams may not detect quality decline, unsafe behavior, failed integrations, rising cost, or unresolved incidents.
Organizations with AI agents or copilots in production.
Digital and AI leaders who need an operating model after launch.
Application owners responsible for availability, support, and change.
Risk and governance teams requiring evidence and oversight.
Operations teams that need measurable, reliable service from AI-enabled workflows.
Establish ownership, service levels, runbooks, access, and escalation paths.
Define the evaluation set, quality measures, business outcomes, cost measures, and safety checks.
Implement monitoring for usage, failures, integrations, latency, cost, and user feedback.
Review outputs and operational incidents with Human in the Lead oversight.
Optimize prompts, knowledge, tools, workflows, infrastructure, and user experience.
Manage releases, support requests, governance reviews, and continuous improvement.
Managed AgentOps service for one or more production agents.
Quality, safety, cost, performance, and usage monitoring.
Evaluation design and recurring regression testing.
Optimization of prompts, retrieval, tools, integrations, and workflow design.
User and technical support with incident and change management.
Governance reviews, evidence collection, and policy updates.
Continuous improvement aligned with business outcomes.
Microsoft Copilot Studio, Azure AI Foundry, Azure services, Microsoft 365, SharePoint, and Power Platform.
OpenAI, Claude, IGNA, Salesforce, ERP, APIs, data platforms, observability tools, ticketing, and reporting systems.
Existing client-built agents where the technical access and operating scope can be agreed.
Security & Governance
AgentOps includes access control, logging, evaluation evidence, incident handling, release controls, change approval, human review, and documented ownership. The governance model is adjusted to the risk and consequences of each use case.
A readiness workshop is the fastest way to find out if this is the right starting point.
Book an AI Readiness Workshop