End AI sprawl.
Know every agent you run.
EARS — the Enterprise Agent Registry — is the trusted system of record for every agent, tool, model and team running inside your business.
In most enterprises, AI shows up everywhere at once: in SaaS tools, in copilots, in shadow automations a business unit spun up last Thursday. Nobody knows who owns what, what it is allowed to do, or what it costs. EARS fixes that by making agents first-class enterprise citizens — with the same rigor you already demand from employees, systems and vendors.
What it is, in plain terms.
Cryptographic identity
Every agent gets a verifiable identifier. Revoke it, audit it, attribute actions to it — the same way you would a human account.
Governed lifecycle
Draft → Sandbox → Active → Deprecated → Revoked. No agent reaches production without explicit approval, review and test evidence.
Semantic discovery
Employees and other agents find capability by outcome — “agents that reconcile invoices” — not by memorizing registry names.
Cost & usage attribution
Token consumption, API calls and run duration roll up by agent, team and business unit. Chargeback and budget control work out of the box.
What changes for the business.
Every model, tool and agent in production is discoverable, owned and governed — no more shadow AI hiding in shared drives.
Discovery and reuse replace one-off builds. Teams compose from a vetted catalog instead of reinventing the same agent three times.
Every agent action is attributable, revocable and logged. Your next audit is a report, not a fire drill.
Enterprise-grade by default.
Decentralized identifiers (DIDs)
Cryptographically rooted identities that survive re-deployment, rotation and cross-environment promotion.
MCP and A2A interoperability
Agents built in different teams and stacks collaborate over standard protocols — no custom glue code.
Approval and review gates
State transitions require named approvers, evidence artifacts and automated checks before they advance.
Secrets and credentials isolation
Agents never hold raw secrets. IAM issues scoped credentials at runtime and revokes them on the fly.
Team and ownership model
Every agent has an accountable owner, a team, and an escalation path. No orphaned automations.
Impact-aware deprecation
Before retiring an agent, EARS surfaces every workflow, app and team that depends on it.
AI that acts on your behalf should be as governed as the humans you trust.
The Inversion Principle says AI should do the work so humans can stay sovereign over intent. But that only works when every agent acting in your name has a known identity, a known purpose and a known boundary.
EARS is the control plane that makes the inversion safe. It turns “we have a lot of AI” into a navigable, auditable, accountable registry — so you can let agents operate at machine speed without losing the thread of who did what.
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