Census
Who’s already at work?
Find every agent across teams, tools, and environments. No roll call required.
The AI workforce company
Grid gives companies the operating model for people and AI to work better together—connecting every agent to its owner, access, cost, and outcomes.
Plot twist: they’re already here
Agents are multiplying across teams, tools, and workflows. Grid gives the company one place to see who’s here—and keep every agent accountable.
Census
Find every agent across teams, tools, and environments. No roll call required.
Ownership
Give every agent a named owner and a reason to exist.
Access
See what each agent can touch—and when those permissions need another look.
Value
Put spend, activity, and business outcomes in the same conversation.
Bring what already works
Connect Claude Cowork, Codex, OpenClaw, Hermes, and the systems they already work in. Grid turns that growing mix into one enterprise view—without asking teams to start over.
Agents already at work
Keep the tools your teams already trust.One place to see every agent, owner, permission, cost, and outcome.
Systems stay in place
Connect the estate without another migration.Enterprise visibility
Five questions every team can answer.Meet Grid
Owners, access, cost, outcomes—all together in one living record.
On the roster
18 agentsThe full story for every agent. Anything unusual moves to the top.
What makes Grid different
One operating layer for the AI workforce already taking shape— across technical teams, business teams, and every system in between.
Claude Cowork, Codex, OpenClaw, Hermes—and whatever comes next.
Ownership, access, activity, cost, and outcomes stay connected.
Templates and frameworks help non-technical teams put AI to work.
Connect the tools people already use without another migration.
See what is running, who owns it, and where attention is needed.
Connect agent activity and spend to the business outcomes that matter.
AI workforce field notes
Practical guidance for the decisions that start after a company brings AI to work.
Explore all field notesA practical model-selection framework built around the work, the quality bar, and the operating constraints that matter after launch.
Tokens explain consumption. They do not explain whether an agent did the right work, used the right access, or produced a useful result.
A practical way to move from token spend and activity counts to the business outcomes that justify an AI agent’s place on the roster.
Start with who’s here
Map what is running, connect the systems it needs, and give every team a clear way to bring AI into the company.