Discover

Every AI agent, accounted for.

Find every AI agent, model, tool, MCP server, and vendor system in use, then land discovery in a governed record, not another dashboard.

Each record carries an accountable owner, risk, lifecycle state, data context, and evidence.

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Shadow AI Discovery

Automatic detection of AI in use across the organization: ChatGPT, Claude, Gemini, copilots, and the agents developers spin up without a procurement touchpoint. Each one surfaces as a governance gap for review.

Multi-vendor chaos is the privacy risk on every enterprise deployment: dozens of agents, vendors, and models. When Agent A calls Agent B via MCP, who owns the output? Multi-source discovery avoids single-signal blind spots.

Cloud billing & SaaS admin signals
AI spend and usage surfaced from cloud cost streams and SaaS admin consoles.
Identity provider & browser telemetry
SCIM signals plus a Chrome extension that sees shadow AI where it’s actually used, in the browser.
Workspace AI scanners
M365 Copilot audit logs, Slack AI app catalog, Notion AI usage, and OpenAI admin scanning.
Agent-level discovery
The Shadow Agent Sentinel scans MCP registries and inspects A2A senders, the agents most platforms miss.
Reconciliation & resolution log
Every discovery moves from discovered to reviewed to registered, accepted-risk, or blocked, with the decision trail kept.
korasafe.ai/discover/shadow-ai
Shadow AI discovery feed with governance gaps Shadow AI discovery feed with governance gaps
6+ discovery signal sources
Shadow AI discovery feed with governance gaps

Supply Chain Visibility

An AI bill of materials for every registered system, covering base models, datasets, inference libraries, vendor APIs, and RAG sources, with continuous vulnerability scanning and vendor risk scoring.

AI libraries carry real CVEs, and most security teams don’t scan them with the rigor applied to application dependencies. KoraSafe™ generates the documentation regulators point toward and watches it continuously.

CycloneDX AI SBOM generation
Aligned to the CycloneDX AI BOM appendix, the format auditors and regulators recognize.
Continuous vulnerability scanning
NVD and OSV scanning with CVSS-mapped severity; matched CVEs become governance findings.
Vendor risk scoring
Vulnerability history, data-handling attestation, geographic residency, and certification status.
Model provenance registration
A historical model-lineage record most organizations cannot reconstruct after the fact.
Regulator export bundle
Provenance and SBOM evidence packaged for technical-documentation requests.
korasafe.ai/discover/supply-chain
CycloneDX AI SBOM with live vulnerability scan CycloneDX AI SBOM with live vulnerability scan
CycloneDX AI SBOM standard
CycloneDX AI SBOM with live vulnerability scan

AI Agent Inventory

Every AI agent catalogued, risk-classified, and lifecycle-tracked. One registry for every agent, its owner, autonomy tier, and data-class footprint: the record everything else attaches to.

KoraSafe is built around the agent. Policies, risk scores, findings, and evidence all hang off the inventory record, so accountability is never ambiguous: every agent has a name next to it.

Registration with autonomy tiers
Sector, jurisdiction, use case, data classes, output type, and declared autonomy ceiling.
Named ownership & RACI
Every agent carries an accountable owner, team, and runbook. No orphaned systems.
Agent Lifecycle Watch
Continuous monitoring keeps the registry honest as agents change, retire, or multiply.
Materiality & impact tiering
Business impact, data sensitivity, and jurisdiction set each agent’s governance scope from day one.
Data-class footprint mapping
Every data class an agent can touch is recorded on the registry entry, so exposure is legible before an incident.
korasafe.ai/discover/inventory
Agent registry with owners and autonomy tiers Agent registry with owners and autonomy tiers
5 lifecycle states per agent
Agent registry with owners and autonomy tiers
Discover

Know every AI agent before it becomes risk.

Find the tools people use, assign ownership, and keep model provenance in one record your team can trust.

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