Solutions
Solve the implementation gap in AI governance.
Uraikkal helps security and governance teams move from uncertainty and disconnected documentation to structured decisions, deployable controls and validated outcomes.
Establish an AI governance programme
Where teams get stuck
AI adoption has outrun the policy. There is a list of tools somewhere, a committee that meets, and no consistent basis for saying yes or no to the next request.
What you do in Uraikkal
Build an application register, define governance categories, assign ownership, capture the rationale behind every decision, and set a review cycle that runs without being chased.
Artifacts produced
Result
A structured governance foundation rather than an informal list of approved and blocked applications.
Govern shadow AI and unsanctioned applications
Where teams get stuck
Employees are already using tools nobody assessed. Blocking everything breaks legitimate work; allowing everything is indefensible.
What you do in Uraikkal
Decide how unapproved and unassessed applications are handled as a category — with a fallback control that applies to the long tail — while approved business use keeps working.
The unassessed long tail is treated as its own governance category with an explicit control, instead of being ignored until an incident makes it urgent.
Artifacts produced
Result
Clear application categories, fallback controls, and a review path for anything new.
Convert AI governance into DLP controls
Where teams get stuck
The governance decision exists on paper. Translating it into what should actually happen when a specific kind of data meets a specific kind of app is still manual, inconsistent, and undocumented.
What you do in Uraikkal
Map data risk families and application categories to explicit actions — allow, monitor, alert, coach, require justification, or block — so every combination has a decision behind it.
Artifacts produced
Result
A consistent control model that engineers can implement without interpreting policy prose.
Engineer Netskope GenAI controls
Where teams get stuck
Someone still has to turn the design into a working policy stack — in the right order, with the right profiles, objects and dependencies in place before anything will save.
What you do in Uraikkal
Generate the policy architecture, recommended policy order, DLP profiles, required objects, user-notification requirements, dependencies and validation steps for the tenant you actually run.
Engineers start from a reviewed policy stack with known limitations documented — not a blank console and a design document to interpret.
Artifacts produced
Result
A consultant-grade Netskope implementation plan.
Prepare for architecture, risk and audit review
Where teams get stuck
The control works, but nobody can explain why it was designed that way, what was assumed, or what happens at the edges — which is exactly what review boards ask.
What you do in Uraikkal
Produce the rationale, assumptions, limitations, testing requirements and supporting documents that technical and non-technical reviewers expect, from the same workflow that produced the controls.
Artifacts produced
Result
Decisions that can be explained, reviewed, challenged and evidenced.
Standardise consulting and service delivery
Where teams get stuck
Every engagement starts from a different methodology and a blank console, so quality depends on which consultant is assigned and nothing carries over to the next customer.
What you do in Uraikkal
Run the same assessment, design, documentation and validation method for every customer, and hand each one a consistent artifact set instead of a bespoke deliverable.
Artifacts produced
Result
Faster and more consistent delivery across customers, without rebuilding the approach each time.
Tell us which problem you're solving.
Onboarding is tailored to the outcome you're after — a governance programme, a Netskope build, or a repeatable delivery method.