Secure AI. Protect Data. From Code to Production.

Secure data, access, and actions behind every AI feature in your product.

< 2 hrs

1,600+ systems and 100+ flows mapped 
— agentless, from day one.

Day 1 to value

Every new agent, AI model, microservice, data pipeline, MCP server, and third-party call lands on the graph the day it appears.

6 surfaces

Code, runtime, AI, data, cloud, identities — one live graph.

What we solve - concrete use case scenarios

Moments every product security teams know

A week on call for product security teams and the specific work Relyance takes off your desk.
Click through the week.

MON
New Agent and Hidden Paths
11:20 · monday
“Did the change create a path from untrusted input to a privileged tool or dataset?”
  • Every release scanned for new paths from untrusted input to privileged tools and sensitive data.
  • Flagged before merge, with the residency, purpose, and customer commitments it would violate.
TUE
Borrowed Identity
10:05 · TUESDAY
“Which human, agent, or service identity will actually exercise that access?”
  • Every agent tied to the exact identities and permissions it runs on.
  • Shared and over-privileged credentials surfaced — and scoped down.
WED
Intent vs Scope
09:14 · wednesDAY
“Is this agent allowed to use this data for this task or goal?”
  • Every data call checked against the task at hand, not just the credential behind it.
  • Valid access flagged the moment it's used outside its intended purpose.
THU
Unintended Data Exfil
14:32 · ThUrSDAY
“Can this data field enter the prompt, context, memory, logs, or model? What is its origin?”
  • Every request resolved in real time — allowed, redacted, masked, narrowed, escalated, or blocked.
  • No static allow-lists; the decision is computed at the moment it matters.
FRI
Silent Drift
18:40 · friday
“Which agents, MCP tools, permissions, and data paths have drifted since you last looked?”
  • Tool access, permissions, and data paths monitored continuously — not audited once a year.
  • New paths and creeping permissions flagged before staffing drops for the weekend.
SAT
Toxic Combinations
08:12 · saturday
“Which agents can combine individually safe capabilities into a dangerous execution path?”
  • Compound risk scored across the graph, not permission by permission.
  • The chain is broken at its weakest link — excess access removed without breaking the app.
SUN
AI Opt-out Assurance
13:47 · sunday
“Can we prove that customer data was isolated, and never used for AI training?”
  • Every data touch logged as verifiable evidence, not policy language.
  • Audit-ready proof on demand — before Monday's questions start.
11:20 · monday
“Did the change create a path from untrusted input to a privileged tool or dataset?”
  • Every release scanned for new paths from untrusted input to privileged tools and sensitive data.
  • Flagged before merge, with the residency, purpose, and customer commitments it would violate.
10:05 · TUESDAY
“Which human, agent, or service identity will actually exercise that access?”
  • Every agent tied to the exact identities and permissions it runs on.
  • Shared and over-privileged credentials surfaced — and scoped down.
09:14 · wednesDAY
“Is this agent allowed to use this data for this task or goal?”
  • Every data call checked against the task at hand, not just the credential behind it.
  • Valid access flagged the moment it's used outside its intended purpose.
14:32 · ThUrSDAY
“Can this data field enter the prompt, context, memory, logs, or model? What is its origin?”
  • Every request resolved in real time — allowed, redacted, masked, narrowed, escalated, or blocked.
  • No static allow-lists; the decision is computed at the moment it matters.
18:40 · friday
“Which agents, MCP tools, permissions, and data paths have drifted since you last looked?”
  • Tool access, permissions, and data paths monitored continuously — not audited once a year.
  • New paths and creeping permissions flagged before staffing drops for the weekend.
08:12 · saturday
“Which agents can combine individually safe capabilities into a dangerous execution path?”
  • Compound risk scored across the graph, not permission by permission.
  • The chain is broken at its weakest link — excess access removed without breaking the app.
13:47 · sunday
“Can we prove that customer data was isolated, and never used for AI training?”
  • Every data touch logged as verifiable evidence, not policy language.
  • Audit-ready proof on demand — before Monday's questions start.

Securing every phase of your AI development cycle

The platform

Three layers of protection.

AI Security

Inventory every agent, model, RAG, & MCP. Detect each one's permission reach. Block the over-scoped agent before it ships — enforced in CI/CD.

Accelerate AI adoption. Safe, governed.

Data Security

Classify sensitive data, watch it in motion, and block it before it leaks — Adaptive DLP that enforces right at your gateways.


Leakage prevented, not investigated.

Privacy

Auto-generate ROPAs and data maps current from live flows. Automate Consent, Assessments, and DSRs end-to-end. Enforce privacy by design in CI/CD.

Always audit-ready, never scrambling.

Powered by Data Journeys™

Real-time data flow intelligence. Code to cloud to AI.

The Data Exposure Graph connects data sensitivity, identity permissions, and AI agent behavior to surface compounding threats that only emerge when you understand the full context.

Customers

What security leaders say

Chris Bender, CISO

“AI is creating and moving data faster than any team can track. Only AI-native tools like Relyance AI can keep up with the discovery and enforcement loop.”

Chris Bender, CISO

Jason James, CIO

“Relyance gives us a complete, contextual understanding of our data landscape. We can see what we have, how it's used, who owns it, and where the risks are. This level of clarity is strengthening our overall security posture.”

Jason James, CIO

Karthik Chakkarapani, SVP & CIO

“Most tools show me a snapshot. Lyo™ gives me the full movie, around the clock. I can't afford to choose between innovation and security.”

Karthik Chakkarapani, SVP & CIO

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See every path AI takes to your data, continuously.

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