Discovery & Policy
See what’s exposed.
Govern it with policy.
Find sensitive data, agents and tools — then define how data is protected, who can see it and what agents can do.
How It Works
Every policy starts with discovery.
Discovery identifies data, agents and tools, how sensitive data is classified and whether it’s protected. Policy then uses those findings to enforce governance without engineering involvement.
Discovery
-
Scan
data and identity sources
-
Classify
knowledge and data
Policy
-
Define
AI + data policies
-
Enforce
distributed policies
Discovery and Policy capabilities
Stage 01 · Discover
Know what exists.
Continuous inventory tracks sensitive data exposure along with every agent and tool deployed.
Native protection awareness checks whether sensitive data is properly protected based on its classification.
Ontology mapping connects every object, protection state, actor and access path to provide a unified view.
Stage 02 · Policy
Set the rules.
Guided workflows define how sensitive data is protected, who can see it and what agents can use.
Policy review flags configuration mistakes and conflicts with approved policies, and each conflict needs a written rationale.
Automatic distribution routes every approved policy to the systems that enforce it, with no manual setup.
What you get
Policies security teams can trust.
An accurate picture of risk.
Data exposure and every deployed agent and tool are verified continuously, so risk ratings reflect what’s actually in place.
Live in minutes.
Governance teams author and approve policies in guided workflows, with no engineering tickets or code.
Consistent enforcement.
One approval updates data protectors, the query gateway and the AI runtime at the same time.
Conflicts caught early.
Policy review surfaces contradictions with existing rules before anything reaches production.
Automation with accountability.
Mappings and policies are proposed automatically, but every change needs human approval and a recorded rationale.
Protection sufficiency
LiveData security
AI security
Discovery that drives enforcement.
Validated protection
Each protection is checked against what the data actually requires, so compliance status is based on evidence rather than assumptions.
One connected inventory
Sensitive data, people, agents and tools are mapped together with their relationships, and the map updates continuously as systems change.
Findings that become policy
Discovery and policy share one platform, so findings turn directly into policies enforced across data protectors, the query gateway and the AI runtime.
Where to start
From first scan to first policy.
Step 01
Scan the environment.
Connect datastores, identity providers, agents and MCP servers to inventory data, protection status, actors and access paths.
Step 01 · Scan
Connected sources
- Datastores Connected
- Identity providers Connected
- Agents Connected
- MCP servers Connected
Step 02
Classify what’s sensitive.
ML models classify data automatically, with confidence scores and a transparent fallback for anything they miss.
Step 02 · Classify
Findings
| Field | Class | Confidence |
|---|---|---|
| PII | 98% | |
| card_number | PCI | 96% |
| date_of_birth | PII | 91% |
| notes | Review | 42% |
Step 03
Set the first policies.
Guided workflows turn findings into policies, which are validated, deployed and enforced on approval.
Step 03 · Policy
Protect PII – Email
- Built from findings
- Validated
- Approved
- Deployed and enforced