About
AI governance should not end with a policy document.
Uraikkal was created to address a recurring problem in enterprise security programmes: organisations can define AI principles, assess applications and publish acceptable-use policies — but converting those decisions into effective DLP controls, implementation plans, testing evidence and operational documentation remains slow, specialist and highly manual.
Mission
Make high-quality AI governance engineering repeatable.
Security teams should be able to make informed AI governance decisions and convert them into defensible, implementable and testable controls — without rebuilding the entire engagement from scratch every time a new application appears.
Uraikkal's governance model, policy architecture and deliverables come from years of hands-on DLP implementation work across regulated enterprise environments. Its workflows reflect how governance decisions, policy architecture, deployment dependencies, testing and project documentation are actually handled in real implementations — productised, rather than reinvented per engagement.
Credibility
Built from real enterprise DLP delivery.
12+
years of DLP and CASB implementation experience
Regulated industries served
Security platforms implemented
What makes Uraikkal different
Governance and engineering in one workflow.
Vendor-neutral governance
Governance decisions are captured as intent, not as one vendor's configuration — so the model survives a change of security platform.
Data-risk-based control design
Controls are decided per data risk family and activity, not per application name. Context determines the action, rather than a blanket rule.
Vendor-specific implementation engineering
The neutral model is translated into the policy topology, order, profiles and objects a specific platform actually needs.
Explainable recommendations
Every recommendation carries its reasoning, assumptions, alternatives, trade-offs and known limitations — so architects can challenge it, not just accept it.
Deployment, testing and evidence
Implementation sequence, test scenarios, expected results and captured evidence are part of the same workflow, not a separate project.
Continuous operational governance
New applications and changed requirements update the affected artifacts, instead of triggering another engagement from scratch.
Our goal is not to remove human accountability. It is to give security professionals a stronger, faster and more consistent way to perform the work.
Vendor support
Netskope now, more to follow.
Netskope policy guidance is available today. Additional DLP, CASB and SSE platforms are planned and will be introduced through vendor-specific implementation packs — they are not available yet, and the site marks them as planned wherever they appear.
See Uraikkal for yourself.
Explore a read-only sample workspace at your own pace. Reach the founding team by email any time you have a question.