Security Leaders
Leadership teams need more than a list of findings. They need a decision-ready story they can explain to executives, auditors, and commercial stakeholders without losing the technical truth.
Explore roleSolutions
Match the platform story to the role, industry, or security question in front of your team.
Tutela helps organizations discover risky AI and data activity, understand what is actually exposed, and govern remediation from a customer-owned control plane.
Buyer journeys
Start with the role that owns the review.
Security leaders, practitioners, and data or AI leaders ask different questions. These role pages surface the evidence, product fit, and next resources that move each review forward.
Security Practitioners
Practitioners do the real evaluation work. If the technical story is fuzzy, the buying motion slows down and the wrong questions dominate the review.
Explore roleData and AI Leaders
AI leaders need to show they can adopt agentic workflows without creating a new blind spot around sensitive data, employee AI use, or auditability.
Explore roleProblem framing
Problem areas
Sensitive data risk
Start by understanding where regulated, confidential, and business-critical data lives and why it deserves attention first.
Access and control context
Review who can reach protected information, how relationships expand exposure, and which access questions deserve a deeper look.
Employee AI governance
Understand how employee AI use changes the review surface when prompts, files, outputs, and policy controls meet protected data.
Industries
Financial Services
Financial-services buyers need to protect customer data and operating discipline while proving they can govern access, AI usage, and sensitive data review without relying on vague product promises.
Explore industryHealthcare
Healthcare organizations need to protect regulated data while making careful choices about access, AI, and deployment fit. That evaluation should feel disciplined, not improvised.
Explore industryTechnology and SaaS
Technology and SaaS companies move quickly, but customer data, product telemetry, internal tools, and employee AI workflows can create exposure faster than review processes can keep up.
Explore industryPublic Sector
Public-sector teams need to balance modernization, sensitive-record handling, procurement discipline, and AI adoption without turning security review into guesswork.
Explore industryUse cases
Sensitive Data Discovery
See where sensitive data lives, understand who can reach it, and prepare better protection decisions with the right data context.
Best for: Security teams, data owners, and cloud teams trying to understand where sensitive data lives and what deserves attention first.
Explore use caseAgentic Workflow Governance
Review agent access, prompt and output risk, and governance expectations before agentic workflows scale.
Best for: Security, AI, and platform teams governing employee AI use, copilots, agents, and model interactions around protected data.
Explore use caseAccess Risk Review
Connect identity, permissions, and sensitive data context so access review becomes easier to prioritize and explain.
Best for: Security and identity teams investigating where access paths create risk across sensitive data environments.
Explore use caseSecure Employee AI Use
Understand employee AI activity, inspect sensitive interactions, and apply policy before everyday AI use becomes unmanaged risk.
Best for: Security, IT, and AI teams deciding how employees can use copilots and AI assistants without creating new data risk.
Explore use caseRecommended reading
Platform Overview
See how Data Security, Agentic Security, and Exposure Validation fit together in one customer-owned operating model.
Open resourceBuyer Guide
See how teams frame the right product conversation, align stakeholders, and prepare the first technical review.
Open resourceArchitecture Brief
Review the customer-owned architecture assumptions and deployment model.
Open resource