Solution
Eliminate Blindspots in Your Technical Estate
Governance teams cannot manage what they cannot see. Shadow AI discovery identifies unmanaged agents and models before they create material liability.
What is Shadow AI Discovery?
Shadow AI Discovery is the automated process of identifying AI systems, LLM wrappers, and autonomous agents that have been deployed outside of an organization's official governance inventory. Beacon utilizes stateless technical observation to detect these hidden assets through cloud spend patterns, API traffic, and container metadata, ensuring your technical estate is always transparent.
"The transition from periodic compliance audits to continuous regulatory intelligence is the single biggest leverage point for AI and biopharma innovators today."
Q.Why does traditional governance miss shadow AI?
Direct Answer
Traditional governance is declarative; it relies on engineers to manually register their systems. In rapid innovation cycles, teams often bypass these steps to move faster, creating a gap between the official registry and the actual technical reality.
Explanation
Beacon bridges this gap by moving from self-reporting to active observation. We don't ask what exists; we observe what is running.
Real-World Example
"Beacon recently discovered an unmanaged agentic stack in a global bank's Marketing Ops unit that was processing sensitive customer data through an unapproved third-party LLM."
The Cost of Invisibility
Silent Liability
Every unmanaged agent is a potential point of data exfiltration or policy violation that human-driven audits will never catch.
Estate Transparency
Bring shadow innovation into the light. Beacon provides the visibility required to govern innovation without slowing down the teams building it.
Immediate Discovery
Initial estate mapping happens in under 48 hours, providing an immediate baseline of your organization's true AI footprint.
Observation vs. Declaration
| Category | Legacy / Manual | Beacon Intelligence |
|---|---|---|
| Discovery Method | Manual self-reporting | Automated technical observation |
| Asset Identity | Human-defined labels | Enterprise Fingerprinting |
| Update Frequency | Quarterly audits | Continuous / Real-time |
| Risk Awareness | Reactive (Post-incident) | Proactive Situations |
The Discovery Process
Signal Ingestion
Beacon ingests metadata from cloud providers, container registries, and API gateways.
Fingerprint Resolution
We resolve technical signals into unique identities to distinguish managed from unmanaged assets.
Registry Cross-Match
Beacon automatically compares observed reality against your existing System of Record (e.g., OneTrust).
Situation Synthesis
Unmanaged assets are birthed as Governance Situations with a full chain of evidence.
Synthesis Engine Active
Enterprise Situations
Shadow Agent Discovery
Identifying autonomous agents deployed in business units without security or governance review.
Orphaned Model Cleanup
Detecting production endpoints that lack a clear technical owner or version lineage.
Frequently Asked Questions
Q: Do you need agents on our models?
A: No. Our architecture is observer-first. We ingest existing telemetry and metadata without interfering with your model runtime.
Q: Which cloud providers are supported?
A: We support Azure AI, AWS Bedrock, GCP Vertex AI, and major internal registries like GitHub and GitLab.
Q: How long does discovery take?
A: Most organizations see their first Shadow AI discovery situations within 24 to 48 hours of connecting their technical sources.
Q: Can we integrate with ServiceNow?
A: Yes. Beacon is an upstream layer. When a shadow asset is discovered, we can trigger a remediation workflow in your existing GRC or ticketing stack.