Black-box actions
Know which agent acted, what it touched, and which downstream system changed.
Agents are already in your org
AI agents are moving fast.
Your visibility is not.
Autonomous agents make decisions, call tools, access systems, and trigger workflows across your product. Without runtime visibility, teams inherit four problems at once.
Unknown failures
Spot failed tasks, retries, degraded outcomes, and reliability patterns before they spread.
Security exposure
Detect unusual access, risky tool calls, data movement, and policy exceptions.
Ownership gaps
Know who owns every agent, with auditable context for decisions, reviews, and controls.
One console · The whole evidence chain
Mission control for your AI fleet.
Every page answers one question from runtime evidence — never from guesswork.
- Runtime — what actually executed, step by step
- Asset Intelligence — every agent, discovered from traces
- Security Intelligence — which agents are risky, and why
- Rules & Alerts — thresholds over runtime behavior
- Gateway Control — recommendations, never auto-enforcement
Runtime evidence, live
Every hop your agent makes
becomes evidence.
An agent reaches an MCP server, the MCP server reaches Slack or your database — ObserveAgents records each hop as a span. Identifiers and timings only, never prompts or responses.
agent → mcp → slack · 3 spans recorded · one trace, end to end — this is the evidence everything else is built from
How it works
From runtime evidence
to recommended control.
One evidence chain: OpenTelemetry traces flow into Runtime, power Asset and Security Intelligence, and end in the Gateway Control Center.
OTel / OTLP
traces in
Runtime
what executed
Assets
inventory
Security
risk, explained
Rules
alerts
Gateway
control, reviewed
Observe first. Control only what matters. Nothing is ever blocked automatically.
The platform
Send traces once.
Everything else appears.
No manual registration, no tagging, no proprietary SDK. Your existing OpenTelemetry stack is the only integration.
Runtime
See what actually executed
Session-grouped traces and per-step execution waterfalls. Structural metadata only — prompts and responses are never stored.
Asset Intelligence
Agents inventory themselves
Every AI system discovered from traces — ownership, capabilities, dependencies, and findings, worst first.
Security Intelligence
Risk, with the evidence attached
MCP tools in production, database and API reach, unknown providers, missing owners — every finding shows why it fired.
Rules & Alerts
Thresholds over behavior
Built-in detection rules evaluate during the intelligence run — never inside ingestion, never enforcing anything.
Gateway Control
Control only what matters
Risky agents become review candidates with suggested controls. The Gateway enforces only when you explicitly configure it.
Integrations
Works with the stack
you already have.
OpenTelemetry is the pipe; the GenAI semantic conventions are the language. If your agents emit traces, ObserveAgents understands them.
OpenTelemetry
OTel Collector
GenAI SemConv
MCP telemetry
Claude Code telemetry
OpenAI SDK
LangChain
CrewAI
LiteLLM
Vercel AI SDK
Any OpenAI-compatible client
Who it's for
Built for the teams
shipping AI agents.
Different teams need different answers. ObserveAgents gives each one the right level of visibility without hiding the technical truth.
Understand what your agents do
See which agents run, what they touch, where they get stuck, and which product workflows depend on autonomous activity.
View the demo →Debug agent behavior from evidence
Runtime timelines, per-step execution waterfalls, tool and MCP calls, errors, and latency — straight from your OpenTelemetry traces.
Explore runtime evidence →Detect risky agent behavior
Investigate runtime security findings — MCP usage, database and API reach, unknown providers, ownership gaps — and review the agents recommended for control.
Review security signals →Ready to make agent activity observable?
Try the ObserveAgents demo: nothing to install — runtime timelines, the AI asset inventory, security findings, and the Gateway Control Center, all on realistic synthetic data.
Try our Demo →
Talk to the ObserveAgents team.
Share a few details and we'll help you explore the demo for your AI agent environment.