01
AI workflow inventory
Where AI is used, who triggers it, what it produces and which business decisions it influences.
AI Risk Due Diligence
Find the risks hidden inside your AI workflows.
Hlinor reviews AI assistants, copilots, LLM workflows and automated decision systems to identify governance gaps, human-review weaknesses, audit-log blind spots and operational risks.
Designed for B2B SaaS, fintech, HR, legal, insurance, compliance and customer support workflows.
What we check
A practical review of how AI is actually used, not a generic ethics memo.
02
Data exposure
Personal, financial, legal, HR, medical, compliance or customer data that enters AI systems or prompts.
03
Human review
Whether people can inspect, override, approve or escalate AI outputs before harm reaches customers.
04
Audit trail
Logs, prompt records, model versions, user actions and evidence needed to investigate incidents.
05
Limitations and claims
Product claims, disclaimers, explainability gaps and places where customers may overtrust the system.
06
Risk reduction plan
Clear recommendations: what to document, monitor, limit, route to humans or redesign.
Good fit
- B2B SaaS using AI assistants, copilots or decision support
- Customer support automation with real customer impact
- Fintech, HR, legal, insurance, compliance or health/wellness workflows
- Companies preparing investor, partner or enterprise-customer conversations
Typical gaps
- No clear AI system inventory
- No documented human-review policy
- No audit trail for AI outputs
- No incident-response path
- Marketing claims stronger than actual controls
Using AI in a sensitive workflow?
Start with a risk review before customers, investors or regulators ask harder questions.