AI Agent Monitoring & Observability Services

AI agent monitoring services give you one consistent view of every agent you run, how each one performs, and what to change next. Wizr AI builds a register of your custom and vendor-embedded agents, then measures each one across six dimensions: accuracy, cost, latency and reliability, risk and compliance, business outcome, and drift. Reporting starts in week one with a weekly executive report to your CEO, CFO, and CTO, and flagged agents are routed to an owner before the next cycle. For a leading US automotive firm, monitoring and weekly optimization lifted dealer support resolution from roughly 25% to the 70% range.

AI agent monitoring tracks what each agent is doing, including its accuracy, cost, latency, errors, and risk signals. AI agent observability explains why, using telemetry such as prompts and responses, tool calls, token costs, versions, and approvals to trace an issue back to its cause. Wizr AI’s AI agent observability services combine both: we measure every agent consistently, then use telemetry and our evaluation harness to explain and fix what the numbers show. Most organizations start with monitoring and add deeper observability where risk, spend, or volume justifies it.

Yes. Monitoring only custom agents leaves a large blind spot, because many agents now run inside licensed platforms. Wizr AI monitors custom-developed agents, including those built on Azure, LangGraph, OpenAI, and Bedrock, alongside vendor-embedded agents such as Salesforce Agentforce, SAP Joule, ServiceNow Now Assist, Microsoft Copilot, Workday, and Adobe. Discovery includes a system and license audit across the vendor platforms you use, so agents switched on inside licensed software are found too. Connectors for Salesforce, SAP, ServiceNow, Azure and OpenAI, AWS and Bedrock, and custom applications feed the dashboards as monitoring matures.

AI agent accuracy is measured with more than one method, because no single test catches every failure. Wizr AI combines human review, golden datasets, LLM-as-judge evaluation, and business rule validation, and adds drift tests and regression suites so changes in quality are caught over time. Results are stored against each agent, so you can compare performance across the enterprise and see trends. When accuracy drops, we update prompts and RAG sources, add golden tests, and route low-confidence cases to human review. Monitoring shows where accuracy falls short; these fixes are what improve it.

AI agent cost monitoring covers platform consumption, model usage, infrastructure, and license cost, attributed to each agent in the register, so every cost spike has an owner. Wizr AI’s dashboards show spend trends, spend by platform, the costliest agents, and right-sizing opportunities. To reduce cost, we right-size models, cache and batch requests, throttle usage, and remove duplicated agent calls. For one client, benchmarking a contract review agent against nine alternative models identified a model with 80% lower cost per contract processed and a 26% faster median response time, with accuracy held.

Wizr AI monitors every agent for four risk signals: PII exposure, policy violations, hallucination, and unauthorized actions. Flagged agents are listed in the weekly report with the specific reason, routed to an owner before the next cycle, and fixed with measures such as limiting privileges, adding approvals, masking PII, and enforcing policy guardrails. Wizr AI is SOC 2 Type II and ISO 27001 certified and supports GDPR compliance. Monitoring makes risk visible, but it doesn’t guarantee compliance on its own, so findings feed into your broader AI governance and oversight.

Yes. In multi-agent workflows, a problem in one agent or tool call can affect the whole process, so each agent needs to be visible. Wizr AI’s multi-agent AI monitoring solutions register every agent in the workflow and capture telemetry such as tool calls, approvals, and versions, so issues can be traced back to the agent involved. As a team that builds agentic workflows, including multi-agent workflows coordinated by a supervisory agent, we understand how agents hand off work. The right monitoring depth depends on how your agents are built and connected, which we assess during discovery.

No. You don’t need perfect observability to start. Wizr AI begins with an agent inventory and sampled reviews, published as a human-curated weekly report from week one. As maturity grows, the report moves to live AI agent observability dashboards refreshed daily, then hourly, with executive and operations views, alerts, and budget guardrails. Connectors are added where risk, spend, or volume justifies the automation, so you only invest in infrastructure that pays off. This keeps the start low-friction while still building toward continuous control.

AI agent monitoring measures how agents perform and where they create risk, while AI governance sets the policies, ownership, and controls that decide what agents are allowed to do. The two work together: monitoring provides the evidence governance needs, and governance decides what to act on. Wizr AI delivers monitoring and observability as part of our AI agent governance services, which also cover the agent register, executive reporting, and governance committee support. Monitoring alone doesn’t create accountability; pairing it with clear ownership does.

The cost of AI agent monitoring services depends on the number of agents, the platforms they run on, how many connectors are needed, how often you need reporting, and how much optimization work is involved. Starting with a human-curated weekly report keeps the initial investment low, and connectors and dashboards are added only where risk, spend, or volume justifies them. Monitoring can also help offset its own cost through cost findings: right-sizing models, caching, and removing duplicated calls reduce spend, as when benchmarking identified a model with 80% lower cost per contract processed for one client.

Look for an AI agent monitoring provider that covers every agent you run, not only the ones a single tool can see, and that turns findings into fixes. Ask whether the provider monitors vendor-embedded agents, how accuracy is measured, which risk signals are tracked, how flagged issues are assigned and resolved, and how quickly reporting starts. Check security credentials such as SOC 2 Type II and ISO 27001. Wizr AI brings a managed service with reporting from week one, six consistent dimensions, an evaluation harness, and results such as a model switch with 80% lower cost per contract and a 25% to 70% resolution lift.

Talk to an AI expert on our team. Tell us which AI agents you know about, where they run, who owns them, and what concerns you most, whether that’s accuracy, cost, risk, or visibility. We’ll start with an agent inventory and baseline, agree on metrics and risk tiers, and publish your first weekly report so you can see the value before expanding. A practical starting point is often your highest-volume or highest-risk agents, with monitoring extending to the rest as the register grows. You can also explore our broader Enterprise AI Services.