From AI demo to production-grade operations.
AgentGuardian and Glacien AgentOps Command Center give enterprises the operating layer they need to monitor, evaluate, govern, and improve AI agents after deployment — so agents stay accurate, safe, cost-controlled, and business-aligned at scale.
What is the AgentOps Command Center?
The operating layer for production AI agents. Monitoring, evaluation, cost control, governance, and continuous improvement — for every agent your enterprise depends on.
Is the agent actually accurate?
Continuous quality evaluation grades every response. Hallucinations and ungrounded answers surface on the dashboard with the trace that produced them.
What is it costing us?
Token, model, retrieval, and tool-call cost tracked per agent, per team, per use case. Spend trends visible — surprises don't happen here.
Did it leak anything?
Every tool call and data access is logged. Sensitive-data exposure is flagged in real time. Audit trail is complete and exportable.
Why did it do that?
Span-level traces show the prompt, the retrieval, the tool calls, and the model decision for every interaction. Reproducible. Reviewable.
Are users actually adopting it?
Adoption, top use cases, unanswered questions, and satisfaction signals visible in one executive dashboard. No guessing on ROI.
Can we prove governance?
Approvals, exceptions, control evidence, and incident history captured for risk, audit, and compliance — automatically, not manually.
Most agents reach production. Few survive it.
A demo is not a deployment
Teams ship impressive prototypes, then can’t answer the next questions: Is it accurate? Is it secure? Is it costing what we expect? Is it actually being used?
Existing tools were not built for agents
APM, SIEM, and dashboards see traffic and errors. They don’t see hallucinations, tool-call patterns, retrieval quality, or whether the answer was actually right.
Cost surprises follow at month two
Token spend, retrieval over-fetch, expensive tools, repeated calls. Without observability, finance learns the bill before engineering does.
AgentOps Command Center is the production layer agents need — quality, cost, governance, and improvement — running every day, in your AWS account.
Run agents safely. Run them efficiently. Make them better every month.
When business, risk, and engineering need to know whether the agents are working — AgentOps answers in one place.
Run safely.
Hallucination checks, RAG-grounding evaluation, tool-use audit trails, sensitive-data egress monitoring, and human approval for high-stakes actions.
Run efficiently.
Token spend, model cost, retrieval cost, tool-call cost, and adoption tracked by agent and use case. Expensive prompts and waste surfaced — before the bill.
Get better every month.
Failure analysis, unanswered-question surfacing, prompt and retrieval tuning, and a structured improvement backlog tied to real usage data.
Five capability modules. One control plane.
Each module sits inside a single platform sharing identity, traces, and evidence. One dashboard. One contract. One source of truth.
Monitor
Tracks usage, success rates, response quality, task completion, latency, and failure patterns across every production agent.
Cost
Token usage, model cost, tool-execution cost, user adoption, and workload trends — by agent, team, use case, and time.
Evaluate
Continuous hallucination and RAG-grounding checks. LLM-as-judge quality scoring against acceptance criteria, in production.
Govern
Prompt and configuration version control. Tool-use audit trail. Human approval workflows for sensitive actions. Failure analysis.
Improve
Monthly improvement backlog built from usage data, user feedback, quality checks, and business priorities — not opinions.
Working software, in your environment.
Each engagement produces running code, dashboards, and operating cadence — not a slide deck.
Six typical AgentOps use cases. Pick the one that hurts most.
Most enterprises land AgentOps on one agent class — knowledge, contact-centre, workflow, or regulated — and expand from there.
Track how enterprise agents perform across departments, workflows, users, and business processes — in real time.
Conversation agents monitored for response quality, escalation accuracy, compliance, sentiment, and resolution outcomes.
Unanswered questions, weak retrieval results, missing content, and outdated knowledge sources surfaced and tracked to closure.
Approvals, API calls, system updates, ticket creation, and business workflow execution captured per agent action.
Logs, evidence, approvals, and exception reports for risk, audit, compliance, and governance — examiner-ready.
Identify expensive prompts, inefficient retrieval, repeated calls, unnecessary tool use, and model-rightsizing opportunities.
AWS-native. Your data, your account.
AgentOps extends Amazon Bedrock AgentCore production capabilities — observability, evaluations, policy, and identity. Traces and evidence stay inside your AWS environment.
Bedrock AgentCore Observability
OpenTelemetry-native traces, spans, sessions, and metrics — consumed straight into AgentOps dashboards and audit logs.
Bedrock AgentCore Evaluations
Continuous quality scoring, hallucination checks, and RAG grounding — automated, not manual.
Identity, Policy, Guardrails
AgentCore Identity, Policy, and Bedrock Guardrails enforce who can do what, with full audit logging.
Analytics & dashboards
QuickSight, OpenSearch, Athena — for executive ROI dashboards, risk indicators, and operational trend reporting.
Four ways to operate at production grade.
From assessment of an agent already in flight, to per-agent managed operations, to enterprise-wide AgentOps, to continuous improvement.
Readiness assessment
- Architecture & observability review
- Risk & operational maturity
- Cost & performance review
- Governance workflow review
- AgentOps roadmap
Per-agent managed service
- Continuous monitoring
- Monthly quality review
- Prompt & config tuning
- Cost review & failure analysis
- Usage reporting
Enterprise AgentOps platform
- Central AgentOps dashboard
- Quality evaluation framework
- Governance workflows
- Risk & compliance reporting
- Executive value dashboard
Continuous improvement service
- Monthly backlog planning
- Prompt & retrieval optimisation
- Tool workflow improvements
- User feedback analysis
- Business value reporting
Procurement via AWS Marketplace — Private Offers and Channel Partner Private Offers supported. Existing AWS commit (EDP) applies.
We operate AI agents like production systems.
Glacien builds and operates multi-agent systems for regulated enterprises. AgentOps Command Center is the running discipline that keeps deployed agents accurate, safe, cost-controlled, and business-aligned — and that closes the gap between agent demo and agent production.
AWS Select Partner with Agentic AI specialisation. Singapore-headquartered with onshore leadership and offshore engineering across India. We do not advise. We build, deploy, operate, and stand behind what we deliver.
Agentic AI, in production.
Ready to move your agents from
demo to production?
Book a 30-minute walkthrough. We will show the AgentOps Command Center on live reference agents, the per-agent operating cadence, and scope an assessment for your strongest production candidate. No slides that waste your time.