A data and AI system inventory
Map data categories, purposes, locations, retention, recipients and AI use cases. Connect each system to an accountable owner and the requirements relevant to its use.
Privacy & AI Governance
Put data and AI under clear ownership.
Know how data and AI move through your organization. Put the decisions, controls and evidence in one working process.
Who we work with
Business, healthcare, education and public-sector leaders managing data, vendors and AI adoption.
Make the requirement part of the work.
Teams adopt tools faster than policies and inventories can follow. Data flows between systems, vendors and models while approval records sit elsewhere. We turn that fragmented picture into a governed operating workflow.
What we deliver
A concrete result at every step.
Working governance processes
Implement intake, vendor review, assessment, approval, human review and privacy-request workflows. Build the records into the process people actually use.
A reviewable evidence record
Maintain assessment inputs, decisions, approvals, exceptions and remediation actions with a source trail and a scheduled review.
The delivery path
From the source to the operating handoff.
System and vendor lists, policies, contracts, AI use cases, existing assessments and the owners of affected workflows.
Explore the core capabilityMap the actual use
Work with system owners to identify data flows and AI-supported decisions, including tools that sit outside the formal inventory.
Build the controls
Translate applicable requirements and organizational policy into permissions, review steps, disclosure workflows and escalation paths.
Test and operationalize
Run representative requests and decision scenarios. Verify routing, approvals and records with the people responsible for them.
Keep it working
Continuity is part of delivery.
New-tool intake, vendor changes, retention reviews and recurring assessments keep the program current as the organization evolves.
Connected to the Axlete portfolio
Explore the product architecture and related work behind our approach.
Related work & methods
Source context
Standards and reporting context
- NIST AI Risk Management Framework
A voluntary framework for structuring AI risk management and review.
- Minnesota consumer data privacy
Statutory source for evaluating Minnesota privacy requirements and coverage.
Connected services
Work with Axlete
Discuss your data and AI governance.
Scope is based on systems, use cases, jurisdictions and workflows. Implementation and recurring operations are defined around the work required.
Discuss your data and AI governance