The pages and data available to you depend on your workspace configuration,
role, and data scope.
Start with one complete investigation
Verify the data foundation, establish a baseline, follow one signal, and turn
the evidence into a concrete next action.
Explore Visibility
Adoption overview
Track engagement, active people, tools, use cases, and changes over time.
People, departments, and tools
Move from organization-wide trends to the people, teams, and products behind them.
Workflows and cohorts
Find recurring work patterns and groups with similar adoption behavior.
Spend
Reconcile contracted, unapproved, and recoverable AI spend.
Activity review
Review captured conversations and coding sessions with scoped filters.
Tool governance
Review tools, access requests, policies, and policy detections.
Build the data foundation
Integrations
Connect supported provider, seat, usage, spend, and telemetry sources.
Endpoint agent
Understand the managed endpoint collection and control plane.
Browser extension and collector
Compare browser activity capture with local coding and agent collection.
Devices, deployment, and privacy
Plan rollout, monitor device health, and apply workspace data controls.
What Visibility helps answer
- Which AI tools are being used, by whom, and in which departments?
- Which workflows repeat, and where is adoption concentrated or stalled?
- Which paid seats are active, idle, duplicated, or outside approved contracts?
- Which tools and access requests need an administrative decision?
- Which collection paths are contributing data, and which devices need attention?
A connected operating loop
Visibility connects observation to action:1
Collect
Bring in provider integrations, managed endpoint signals, browser activity,
local collector data, or model traffic configured for your workspace.
2
Resolve
Associate activity with people, departments, accounts, tools, and devices.
3
Understand
Compare adoption, workflows, activity, and spend across the scope available
to your role.
4
Act
Review tools, respond to access requests, adjust policies, reclaim spend,
and improve deployment coverage.
Review the data-source architecture
See how endpoint, browser, local, integration, and model-traffic data fit together.