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Agent estate
Microsoft, AWS, Google, SaaS, and custom agents become one operating view.
Solutions
Govern AI agents where enterprise risk actually shows up.
Tegrix is used when an AI agent can touch data, invoke tools, move money, change systems, approve work, or affect a customer outcome.
For CIOs: one operating view across agent platforms.
For security and risk: controls before sensitive actions execute.
For audit and regulators: evidence tied to the decision, not reconstructed later.
Enterprise workflows
Where agent control becomes unavoidable
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Sensitive action
Data export, access, refund, code deploy, and system-change actions are reviewed before execution.
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Evidence
Decision, context, control, execution state, and proof remain attached.
Solution takeaway: the risk is not “AI” in general. It is an agent taking an enterprise action before the enterprise has decided.
Solutions takeaway: the buyer should see the action, the control point, and the evidence left behind.
Where Tegrix is pulled in
The moments native consoles do not cover.
Native consoles are useful inside their own boundary. Tegrix matters when the action crosses platforms, owners, policies, systems, or evidence requirements.
Enterprise agent inventory
See which agents exist, who owns them, what platform they run on, and where ownership or policy coverage is missing.
Outcome: one inventory across agent platforms.
High-impact action control
Apply controls to sensitive exports, privileged access, production changes, refunds, approvals, and agent-to-agent context handoffs.
Outcome: sensitive actions are decided before execution.
Audit-ready evidence
Keep the request, resolved facts, matched control, outcome, execution state, and immutable evidence record together.
Outcome: audit review starts from the decision record.
Connection packages
Connect through provider APIs, SDKs, adapters, wrappers, gateways, and read-only sync where each workflow requires it.
Outcome: control is added where the workflow needs it.
Industry relevance
The same control point. Different business consequences.
Finance, healthcare, government, retail, manufacturing, and services teams do not worry about the same agent action. The control model is consistent; the consequence is not.
Finance & Accounting
Drafted finance work across close, reporting, payments, cash, receivables, FP&A, and finance master data.
Control language
Closed periods, materiality, reporting tie-outs, payment authority, supporting evidence, segregation of duties, and final outcome evidence.
Healthcare
Agents touching PHI, claims, prior authorization, revenue cycle, clinical operations, or patient-facing workflows.
Control language
HIPAA, PHI boundaries, minimum necessary access, owner accountability, audit trail.
Government contractors
Agents that use controlled data, privileged identities, subcontractor workflows, or authority-bound processes.
Control language
RBAC, ABAC, authority boundaries, evidence packages, deployment boundary options.
Retail and commerce
Agents that approve refunds, export customer lists, change promotions, touch loyalty data, or act in customer channels.
Control language
PII, PCI-adjacent workflows, approved destinations, customer-impacting action review.
Manufacturing
Agents involved in supplier operations, quality exceptions, maintenance workflows, code changes, or plant systems.
Control language
Operational continuity, production-change approval, supplier access, system-of-record evidence.
Professional services
Agents summarizing client work, moving documents, drafting deliverables, or sharing context across teams.
Control language
Client confidentiality, data handling, workspace boundaries, reviewable decision records.
Buyer questions
What teams ask before they scale agent use.
The answer should be concrete: where the agent runs, what action is controlled, what evidence remains, and how much the environment has to change.
Why not Microsoft, AWS, or Google alone?
Each platform sees its own world. Tegrix gives the enterprise view across provider boundaries.
Is this generic GRC?
No. The control point is the agent action: allow, hold, block, monitor, and retain evidence.
Will this require rewrites?
No rewrite to begin. Start with source visibility, then add SDKs, adapters, wrappers, or gateways where control is needed.
Can regulated teams use it?
Regulatory language maps to controls and evidence; Tegrix should not claim a certification your environment has not validated.
Is there a technical wedge?
Runtime decisions use live enterprise context before a high-impact action proceeds.
Is this real enough to evaluate?
The right evaluation is a real workflow, real source evidence, real control behavior, and a retained decision record.
Next step
Map Tegrix to an agent action your teams already worry about.
Start with a data export, access request, production change, refund approval, clinical operation, claims process, finance action, or custom agent action. Tegrix should show what exists, what control applies, and what evidence remains.