# 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](/docs/introduction-to-relyance-ai/relyance-ai-capabilities/)**: what each capability does and how the pieces fit.
- **[Capabilities in Depth](/docs/introduction-to-relyance-ai/capabilities-in-depth/)**: features and use cases, including the five privacy modules.
- **[How Relyance AI Works](/docs/introduction-to-relyance-ai/how-relyance-ai-works/)**: the Data Journeys graph, the systems it connects, and where enforcement runs.