Product / AI agent observability

See what your AI agents do after you ship.

Find silent failures, recurring issues, and users who need help. Connect your existing traces to understand what happened across sessions and releases.

a successful trace can still disappoint a user

24M+ messages ingested

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Agent fleet

Know which agent needs attention first.

Compare traffic, evaluated success, issue-free sessions, open issues, setup state, and current versions across every observed agent.

Agent fleetProduction · last 7 days
Agents with traffic4Production chats37.6kIssue-free87.9%Agents to review2
AgentTrafficIssue-freeOpen issues
Example workspace with synthetic data

Issues

Separate broken behavior from broken infrastructure.

Start with the problem in plain language, quantify its impact, review likely cause and next action, then open representative production sessions.

IssuesActual problems, not detector definitions
ProblemIncidenceLast seen
Example workspace with synthetic data

Search and sessions

Move from a question to the exact production object.

Search across users, sessions, issues, agents, MCP servers, saved groups, releases, and coding-agent activity without building another dashboard.

Workspace analyst

Ask a production question in plain language.

The in-product analyst can use the same bounded workspace capabilities available through the Flowlines MCP server, then return a grounded answer, chart, and product objects to inspect.

You

What changed in production this week?

✓Read workspace context✓Compare 7-day metrics✓Inspect releases✓Open related issues
Flowlines

CRM Agent quality fell after crm-3.2, while Coding Assistant adoption and verification both increased.

Evaluated successCurrent 7 days · change vs previous

CRM Agent72%-7 pts

Research Agent79%-2 pts

Support Copilot88%+1 pts

Coding Assistant90%+6 pts

Example workspace with synthetic data

Releases

Read the production receipt after every change.

Compare issue-free rate, evaluated success, and review volume, then inspect the prompt difference, related issues, and chats observed after deploy.

Grouped byrelease.version
4,642 matching sessions · last 30 days
Selected production grouprelease/1.9

1,786 sessions in this production window.

Evidence from release/1.9

Chats behind the difference

Select a version above to change the evidence window

Prepare the Acme briefNo issue detectedSuccessful

Find platform engineersRecovered after one retrySuccessful

Sync qualified leadsThree repeated tool callsNeeds review

Go deeper

Three specialized operating views.

Users and cohortsSee adoption, activity, outcomes, and issues for every person and group.Explore user analytics ›MCP observabilitySee server inventory, tool adoption, clients, identities, calls, and complete journeys.Explore MCP analytics ›Coding-agent usageMeasure adoption, cadence, delegation, verification, retries, and task context by developer.Explore AI usage ›

Use Flowlines with your assistant

Run production agents with the full picture.