# Relyance Ai

**Canonical:** https://apis.io/providers/relyance-ai/  
**Website:** https://relyance.ai  
**APIs profiled:** 0

Relyance AI is an AI-native data security, AI security, and privacy platform that maps data flows from source code through cloud and SaaS systems to AI models. Its core product, Lyo, acts as a "data defense engineer" providing real-time visibility into where sensitive data lives and moves, who accesses it, and how to remediate risk. The platform unifies data security (sensitive-data discovery, classification, and exfiltration detection), AI security (AI agent inventory, MCP server discovery, agentic AI risk), and privacy automation (DSRs, ROPAs, DPIAs, and consent management). Relyance AI is backed by Menlo Ventures.

## Kin Score — 18.2 / 100 (emerging)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 18.2).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 18.4 |
| Developer Ergonomics | 14.3 |
| Commercial Clarity | 39.5 |
| Access Clarity | 39.5 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (2)

- **Relyance Ai Domain Security** — TLSv1.3 · HSTS · DNSSEC · DMARC
- **Relyance Ai Trust Center** — SOC 2, ISO 27001

## Tags

Company, Data Security, Privacy, AI Security, AI Governance, Data Governance, Compliance, Consent Management, Data Discovery

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/relyance-ai/). Scores are computed from the provider's own public artifacts under a published rubric.