Managed AI agent operations: how Nestack Agent Care runs production agentsannouncement
Nestack Agent Care now publishes its updates here. This first note explains what managed AI agent operations means in practice and how the service is organised.
Running AI agents like production systems
Most teams can build an AI agent. Keeping it reliable once real users and real workflows depend on it is a different job. Nestack Agent Care operates production AI agents across their goals, workflows, tools, LLMs, evaluations, guardrails, human review and business outcomes. The aim is to detect failures early, manage policy risk, watch for performance drift and verify that every improvement actually holds as conditions change.
What the operations cover
- End-to-end tracing and telemetry so each agent run can be inspected step by step.
- Evaluation runs and verification loops that check agent output against defined eval sets instead of relying on spot checks.
- Tool action monitoring and verified guardrails, so agents only act within the limits a business has approved.
- Staffed human review for cases that should not be decided by a model alone.
- Incident response, plus cost and drift controls, with a 30-minute critical SLA for enterprise customers and continuous 24/7 coverage.
Industry and department playbooks
Agent failures look different in accounting, healthcare, banking, retail or logistics. Nestack Agent Care keeps playbooks for 23 industries, plus department playbooks for teams such as customer support, finance, HR, IT, legal and sales. Each playbook lists the failure modes being monitored, the evaluation sets that are run and the procedures followed when something goes wrong.
Where to learn more
If your organisation already has agents in production, or is about to launch them, the overview, playbooks, procedures and pricing are on the managed AI agent operations site, where you can also request a free demo.