Scattered assistants
Different teams adopt different assistants, with no shared structure or oversight.
Tracey Enterprise
Manage who can use which agents, what those agents can access, which tools they can call, what policies apply, and where the work is saved — all in one private workspace.
Use trusted AI engines underneath. Keep the company layer governed and in one place.
Tracey Enterprise is a governed AI operations layer — not a generic SaaS tool.
The problem
AI usage spreads fast, and so does the fragmentation. The cost is rarely the model — it's the lack of a layer around it.
Different teams adopt different assistants, with no shared structure or oversight.
Sensitive files get copied around and prompts run ungoverned across tools.
Useful work disappears into chat logs, and sensitive tools run without approvals.
There's little record of who used which capability, on what, or why.
The model
Instead of every employee assembling their own AI setup, admins define the workspace once: who the users are, which agents exist, what files and workspaces they touch, which tools and integrations are available, and what gets reviewed or approved.
One governed layer, defined by admins.
Agents
Agents are shaped around the work a team actually does — not one generic assistant trying to cover everything. Each one carries the properties that make it governable.
Illustrative mapping. Admins define the roles, agents, and access that fit the company.
Security
Rather than one perimeter, Tracey Enterprise layers controls from who a user is all the way through to what is recorded.
Every request is tied to an authenticated user.
Each user reaches only the agents and areas they're granted.
Work stays inside the workspace boundaries it belongs to.
Agents operate within a defined role and remit.
Which tools an agent may call is explicitly controlled.
File and artifact access is scoped to what's permitted.
A lightweight policy check can run in front of execution.
Sensitive actions can require a person to sign off.
Outputs and actions are kept as durable, reviewable records.
Before a prompt reaches a powerful agent or a sensitive tool, the request can be checked — a policy checkpoint in front of execution.
Compliance
The controls that make AI auditable are built into the way work already flows — not bolted on as a separate process.
In practice
Controlled user access and scoped agents keep usage inside its remit. Approval checkpoints and sensitive-tool restrictions sit in front of risky actions. Durable artifacts, saved plans, and job history make the work reviewable after the fact.
Policy-aware, auditable, and company-owned.
Capabilities
Connect the capabilities a company already relies on — and manage how they're used from one place.
External AI services and business apps connect into the workspace, so they're reached through governed agents rather than scattered logins.
Plugins and MCP servers extend what agents can do, while admins decide which agents may use them.
Local scripts, APIs, and internal systems become callable capabilities — under the same access and policy controls.
One place to manage how capabilities are used.
Durable work
The point of governed AI work isn't a stream of answers — it's a growing body of company knowledge. Tracey is designed to preserve plans, reports, files, artifacts, history, job results, workflows, agent instructions, and operating knowledge.
Tracey Enterprise
Tracey Enterprise gives companies the layer they need around AI: users, agents, tools, files, security, compliance, workflows, and durable outputs.
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