Every cost line has an owner and a return. AI has neither.
ExecPath gives enterprises a single, provider-independent view of every AI agent, seat and workflow: who owns it, what it costs and what it returns.
AI adoption has outpaced governance.
Teams build and license AI tools across several providers, usually without a shared record of what exists. Leaders are asked to report AI spend and return to their boards, and the data to do so is not available in any single system.
Agents without owners
Agents and workflows run with no assigned owner, no telemetry and no review.
Duplicated spend
Different teams and providers pay for tools that perform the same function, across both seat licenses and metered consumption.
No measure of return
Usage dashboards report activity. They do not show what AI costs in total or what it delivers.
One registry, one cost view, independent of provider.
ExecPath connects to the platforms an organization already uses and normalizes what it finds into a single schema, so that ownership, cost and overlap can be reviewed in one place.
Registry
Every agent, application and workflow across providers, with owner, provider, status and telemetry coverage.
Cost
Spend by department, provider and agent, covering seat licensing and metered consumption.
Overlap and shadow AI
Duplicated and unmanaged agents identified and quantified, with a dollar figure attached.
Cost is the foundation. Once spend is attributed to owners and workflows, it can be compared with the outcomes those workflows produce.
Connect
Your administrators generate read-only credentials in your own tenant, using our minimum permission list.
Discover
Collectors inventory agents, seats and consumption across providers and normalize them into one schema.
Report
You receive the complete AI registry and a quantified view of duplicated and shadow spend.
Read-only, metadata only, controlled by the customer.
Access runs through credentials created and revoked inside the customer’s own tenant. Every request is visible in the tenant’s native audit log.
In scope
- Inventory: agent and workflow names, owners, providers, status, creation dates
- Licenses and usage: assigned seats, license type, last-activity signals
- Consumption and cost: token counts, credit use, spend by workspace and model
Out of scope
- Content: no prompts, conversations, documents, emails or files
- Outputs: nothing that an agent or copilot produced for your teams
- Write access: ExecPath cannot create, change or delete anything in your environment
Building against real environments, with a small group of partners.
ExecPath is onboarding a limited number of design partners. Participants get early access and direct influence on the roadmap, and keep the full picture of their AI estate whether or not they continue.