Teramind launches agentic AI visibility and policy platform for AI tools
Updated 12:45 EST / March 03, 2026
Teramind announced its AI Governance platform, built to give companies behavioral oversight of AI agents and tools operating alongside employees. As AI starts acting like a co-worker, visibility and policy control move from "nice to have" to non-negotiable.
Teramind's Internal Research Team reports that over 80% of workers use unapproved AI on the job, one-third have shared proprietary data with unsanctioned services, and 49% actively hide their AI use from IT. That's not a tech shortage-it's an oversight problem.
"This isn't a technology gap - it's a governance gap," said Isaac Kohen, chief product officer at Teramind. "The answer isn't less AI. It's governed AI."
The shift is already here: worker access to AI rose 50% in 2025, and 23% of organizations are deploying autonomous, agentic systems. Shadow AI isn't a fringe issue-it's spreading across teams and tools.
What Teramind's AI Governance platform does
- Provides instant visibility into the AI layer: captures prompts, responses, and autonomous behavior across ChatGPT, Microsoft Copilot, Google Gemini, and shadow AI tools.
- Sees and logs anything an AI tool or agent does via text capture, screen recording, OCR, and full transcripts of agentic activity.
- Requires no new infrastructure; it runs on what you already have.
- Generates automatic audit trails aligned with FedRAMP, SOC 2, ISO 27001, EU AI Act, and HIPAA expectations.
Why this matters for IT, security, and product teams
Unapproved AI use creates blind spots that traditional monitoring misses. That's where sensitive prompts, model outputs, and agent actions slip through.
According to Teramind's Insider Risk Management Team, AI-linked breaches and leaks now cost more than $650,000 per incident. That figure often excludes long-tail exposure: data reuse in training sets, prompt leakage, and automated actions gone wrong.
Compliance is tightening. You need verifiable audit trails of who did what, which model was used, what data moved, and why. If AI behaves like a teammate, it needs the same accountability.
Practical steps to reduce AI risk now
- Inventory usage: identify every place prompts and agent actions exist across ChatGPT, Copilot, Gemini, and internal tools.
- Capture context: log prompts, responses, and agentic actions with transcripts and screens for full-chain evidence.
- Set clear policies: define approved tools, model access, and data classes; flag or contain unsanctioned use.
- Integrate with security: route AI logs to your SIEM, add detections for sensitive patterns and exfiltration paths.
- Create an approval path: standardize requests for new AI tools, enforce reviews, and train teams on safe usage.
Questions to ask any AI governance vendor
- Can you observe agent actions across desktop, browser, and API without breaking workflows?
- How do you capture prompts and responses across multiple tools, including shadow AI?
- Do you produce audit trails mapped to FedRAMP, SOC 2, ISO 27001, EU AI Act, and HIPAA?
- How are data retention, user privacy, and role-based access handled?
- What's required to deploy-do we need proxies, gateways, or extra infrastructure?
The bottom line
AI is now a participant in your workflows. Treat it like any other user: visibility, policies, audit trails, and consequences. Teramind's approach-seeing prompts, outputs, and agent actions across sanctioned and shadow tools-helps close the governance gap fast.
For deeper, role-specific guidance on implementing AI oversight and integrations, see AI for IT & Development and AI for Product Development.
Your membership also unlocks:
