What is Relyance AI?
Relyance AI helps customers secure and govern data, access, and actions behind every AI feature in their products.
The problem
AI writes a growing share of your code, and the code you ship now embeds AI: agents, model calls, RAG pipelines, MCP servers. Each of these can reach data along paths nobody drew in a design review. The paths are non-deterministic: an agent decides at runtime what it calls and what it reads.
The exposure multiplies across three dimensions: AI, data (structured and unstructured), and identities (human and non-human). AI-generated code, agents, and prompts have grown roughly 10x, and so have identities, scopes, and permissions.
What Relyance AI does
Two capability pillars, one graph.
AI Security and Governance. Relyance classifies data, maps data flows, fixes risky flows and unsafe access, and automates AI governance. At runtime, it keeps AI within bounds: it blocks data misuse, prevents data leaks, and allows only the AI actions your company and the app developer approved.
Privacy Automation. Relyance generates ROPAs and data maps from live flows and automates DSRs, assessments, and consent. Your records match production on the day a regulator asks.
Both run on our Data Journeys graph. You seamlessly integrate with systems you already run: code, cloud, data platforms, identity, AI providers, SaaS. The graph stays current as they change.
Where next
- Relyance AI Capabilities Overview: what each capability does and how the pieces fit.
- Capabilities in Depth: features and use cases, including the five privacy modules.
- How Relyance AI Works: the Data Journeys graph, the systems it connects, and where enforcement runs.