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Enterprise

Enterprise control for AI support operations

A security-first support cockpit for teams that need tenant isolation, approval gates, audit evidence, and provider visibility before scaling AI-managed support.

Governance
Visible

Policy, approval, and audit live in the product.

Security
Layered

Auth, signatures, tenant isolation, and executor gates work together.

Scale
Controlled

Durable work and queues absorb support load without hidden autonomy.

1.0

Govern AI without pretending it is an employee

Tier0 keeps AI useful and bounded. It can classify, summarize, draft, cite, and propose actions while humans and deterministic policy own outcomes.

  • Human approvals
  • Policy versioning
  • Structured AI outputs
2.0

Operate across teams and products

Enterprise teams can centralize support posture while projects keep their own domains, sender identities, sources, and rules.

  • Project isolation
  • Workspace roles
  • Provider readiness
3.0

Keep compliance review boring

Audit trails connect proposals, decisions, actors, policy, model metadata, and executor results so review is precise.

  • Immutable event chain
  • Entity filtering
  • Redacted details
Operations

What this means in production.

These pages describe the product contract behind the UI, not a decorative brochure. Each surface should connect back to the same governed support loop.

Control boundary

No provider tokens in client UI.

Operator workflow

Support moves through secure ingest, AI preparation, human approval, outbound execution, and audit evidence.

Configuration impact

Provider setup, project policies, knowledge trust, retention, and billing limits decide how this behaves for a real workspace.

Proof points

Designed for governed support, not hidden autonomy.

No provider tokens in client UI.
No model-owned side effects.
Auth is revalidated beyond route interception.
Next

Keep exploring the operating model.