Paving the Road to Production: Governed Enterprise AI Agents — Harish Gaggar, Credit Karma
Register an agent through an internal portal and receive more than a repository: the deployment also needs identity, memory, traces, evaluations and secret handling.
Harish Gaggar walks through that paved path for enterprise agents at Intuit Credit Karma. Local development progresses through container builds, review, security scanning and Kubernetes deployment, with the supporting resources provisioned consistently. The architecture places a centralized MCP gateway between agents and tools so authentication and routing are part of every request. Custom MCP servers expose reviewed tools, while OpenTelemetry, Tempo, Prometheus and Grafana make failures, latency and access behavior visible. Gaggar then follows a LangGraph workflow from interpretation and planning through evidence gathering, policy checks and human approval for sensitive actions. Threads, runs and checkpoints preserve state, while separate tracking tables record model use, tool calls, costs and evaluation fields. Demonstrations inspect those records rather than establish a validated quality score for the whole system.
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