Capabilities in Depth
Everything below runs on the Data Journeys graph, which maps the paths to your data across code, cloud, identities, and third parties.
AI Security and Governance
Component 1: AI Governance
Discover AI, classify data, and map flows. Understand access and data use. Close risky exposure, enforce policy, and automate AI governance and data posture management.
| Features | Use cases |
|---|---|
| Discovery of every AI agent, model, RAG pipeline, and MCP server | Answer, with evidence, which AI paths can reach customer data |
| Context-aware classification of structured and unstructured data at petabyte scale | Build an accurate picture of the sensitive data you hold |
| Data flow mapping from code to cloud to third party | See where every sensitive field goes |
| Access and data-use analysis: permission reach and provenance per component | Know what each agent can touch before you approve it |
| Policy enforcement at merge in CI/CD, with impact analysis and a fix per finding | Close risky exposure before it ships. Continuous monitoring in production. |
| Automated AI governance and data posture management | Keep AI and data posture current without manual reviews or querying the business |
Component 2: AI Evals and Runtime Guardrails
Generic and open-source safety evals don't know your pricing, customers, business goals, constraints, or policies, so they don't hold up in production. Relyance builds custom evals and runtime guardrails for your business and each AI use case. The evals run before every release, and the same rules run as guardrails in production.
| Features | Use cases |
|---|---|
| Custom AI evals generated and contextualized to your business and use cases | Test the behavior and safety that matters to your business and is specific to your AI use case, not a generic benchmark |
| Evals run before every release | Catch a wrong answer, bad action, unsafe activity, or regression before customers see it |
| Alignment enforcement | Keep AI outputs and actions within your business goals and constraints |
| Data exfiltration blocking | Stop a leak before data leaves your environment |
| Prompt injection prevention | Stop a crafted input from hijacking an agent |
| Unauthorized action blocking | Ship agents that take only the actions you approve |
Privacy Automation
Five modules automate privacy work.
Universal ROPA
Most ROPAs describe systems as they were at the last review; this one regenerates from live flows.
| Features | Use cases |
|---|---|
| Records self-update from live data flows | Survive a 48-hour GDPR Article 30 audit |
| Multi-jurisdiction coverage | Pass privacy diligence during M&A without a scramble |
| Lawful basis and retention tracked per activity | Run a current ROPA without a team maintaining it by hand |
Data Mapping
Data Mapping builds the map from your systems themselves.
| Features | Use cases |
|---|---|
| Automated mapping | Track data inventory, usage, and flow without manual upkeep. No need to survey the business |
| Multidimensional classification | Know your crown-jewel data, where it lives, and how long you keep it |
| Drift detection | Catch data misuse when a flow changes |
DSR Automation
A data subject request is a distributed systems problem: the requester's data sits across SaaS tools, databases, and internal APIs, and the clock starts when the request lands.
| Features | Use cases |
|---|---|
| Unified request portal with identity verification | Verify who is asking before you move any data |
| Autonomous fulfillment across SaaS, databases, and APIs | Meet GDPR and CCPA deadlines through a spike in requests, without hiring |
| Audit log per request | Show a regulator exactly what you did, and when |
Assessments
Regulators add assessment obligations faster than privacy teams add headcount.
| Features | Use cases |
|---|---|
| Automated DPIAs, PIAs, and AI risk assessments | Finish DPIAs, PIAs, TIAs, and AI risk reviews before launch |
| Live obligation-gap detection | Catch obligation or control gaps from applicable regulations or compliance frameworks |
| Risk scoring | Cover thousands of assessments with a small team |
Consent Management
A correct cookie banner cannot cover trackers you do not know are running.
| Features | Use cases |
|---|---|
| Tracker discovery and governance | Catch a tracker sending health data before it becomes an incident |
| Consent provenance | Prove what a user consented to, and when |
| Audit-ready consent vault | Walk into a cookie audit with the evidence already filed |
How it fits together
Close an unsafe flow and the graph updates: the ROPA reflects the change, and the related assessment gap closes. For the mechanics, read How Relyance AI Works.