Visibility before enforcement
Start read-only, understand what exists, and prove value before inline controls expand.
Company
Tegrix exists because agent control cannot live inside one platform.
Enterprises are adopting AI agents across copilots, cloud platforms, SaaS tools, frameworks, and custom applications. Platform controls matter, but enterprise accountability has to span all of them.
Know which agents exist and who owns them.
Apply authority and controls before high-impact actions run.
Keep evidence that explains what happened.
Company point of view
Enterprise accountability across fragmented AI platforms
Enterprise AI is being deployed platform by platform.
Accountability, authority, and evidence have to operate across the enterprise.
Tegrix was created to close that gap.
The enterprise problem is not model access. It is operating authority.
Once agents can touch data, call tools, trigger work, change systems, or affect customers, governance can no longer be a document reviewed after the fact. Enterprises need a way to see agents across platforms, assign ownership, apply controls, and retain evidence when actions matter.
Built for the teams responsible after the demo ends.
Tegrix is designed for the enterprise teams that have to operate AI safely when prototypes become access, spend, system change, customer impact, and audit questions.
CIO
CISO
Head of AI Platform
Enterprise Architecture
Security and Risk
Compliance
Internal Audit
Business Owners
Operating principles
How Tegrix thinks about enterprise AI control.
Evidence before opinion
Control gaps, exceptions, and decisions should point back to source evidence and ownership.
Cross-platform by default
Agent control cannot stop at one model provider, cloud, SaaS platform, or framework.
Runtime where it matters
Policies become governance when high-impact actions are controlled at the moment they happen.
Founder
Founder-led around the enterprise control gap.
Senthil Kumar, Founder & CEO
Tegrix is led by Senthil Kumar with a focus on helping enterprises govern, observe, and control AI agents across fragmented environments. The company point of view is direct: as agents become part of business execution, enterprises need accountability, authority, and evidence across the platforms where agents operate.
LinkedIn profile