Understand AI use
See how employees, assistants, and agentic tools are actually using AI.
Visibility, capabilities, and controls for AI use Learn more →
See how AI is being used. Control what happens next.
3LS gives teams visibility into AI interactions, detects sensitive content, understands intent, and applies controls when behavior crosses a line.
- Understand
- AI use
- Detect
- Sensitive content
- Apply
- Controls
Single story
One interaction. Clear understanding. Better decisions.
Interaction
An employee asks AI to summarize a customer export.
Intent
Data handling
Sensitivity
PII detected
Control outcome
Warn the user, record the event, and route it for review.
Mechanism:
On-device agent intercepts AI activity before it leaves the endpoint.
Privacy:
Detections and policy decisions stay within your organization.
Detect sensitive content
Spot PII, secrets, and risky interactions before they move further downstream.
Apply controls
Choose when to allow, warn, or block and give teams evidence for every decision.
How it works
Move from vague AI risk to visible, understandable decisions.
Instead of treating AI as a black box, 3LS helps teams understand how AI is being used, where sensitive data is involved, and when controls should step in.
1
Next
AI interaction begins
A person or tool sends content to an AI assistant, model, or connected workflow.
2
Next
Intent is understood
3LS classifies what the interaction is for and how the AI is being used.
3
Next
Sensitivity is detected
Sensitive content and risky behavior are surfaced before the interaction becomes an incident.
4
Controls are applied
Teams can allow, warn, or block based on context, risk, and policy.
What the story answers
Three questions every security team needs answered
Prompt classification answers how your users are using AI. Sensitive-content detection answers what information is present. Controls answer what should happen next.
Prompt classification
How are your users using AI?
Classify drafting, coding, research, data handling, and tool-driven behavior into clear operating patterns.
Outcome: Visibility into AI usage
PII detection
What sensitive data is present?
Highlight personal information, secrets, and restricted content inside prompts, tool inputs, and outputs.
Outcome: Fewer accidental exposures
Controls
What should happen now?
Apply allow, warn, or block decisions that match the interaction, the sensitivity, and the business context.
Outcome: Consistent outcomes
Operator view
Turn AI interactions into clear decisions
Give security teams a readable trail of what was detected, what it meant, and what action was taken.
Recent findings
Intent, sensitivity, and control outcomes
3 decisions captured
Activity
Intent
Sensitivity
Action
Customer records pasted into an assistant
Data handling
PII detected
Warn
Prompt requests external tool access
Tool use
No sensitive data
Allow
Prompt includes an API token and a request to share it
Data sharing
Secret detected
Block
Solutions
Go deeper on the capabilities behind the story.
Start with one visual story on the homepage, then explore the capabilities that help teams understand AI use, detect sensitive data, and apply the right controls.
Prompt classification
Understand how your users are using AI
See whether AI is being used for drafting, coding, research, summarization, data handling, or tool-driven work.
Explore capabilityPII detection
Spot sensitive data before it spreads
Surface personal information, credentials, and restricted content inside prompts, tool inputs, and outputs.
Explore capabilityAI controls
Choose the right action for each interaction
Apply allow, warn, and block decisions based on context so teams can guide AI use without slowing everyone down.
Explore capabilityFrom the blog
Start With the Research
A few articles that explain the operating model behind the product: where AI use becomes visible, why incidents expand, and how control decisions should be made.
Thought Leadership9 min read
AI Chat Trust Collapse and the Shadow Database Problem
Users experience AI chat as a private workspace, but providers and operators control the storage, sharing, indexing, and failure modes around the transcript.
Read article →
Thought Leadership8 min read
The Enterprise AI Visibility Gap Is the Real Incident Multiplier
After an AI exposure, the hardest question is usually what your own organization cannot answer: where AI is active, what was pasted in, and what was shared.
Read article →
Thought Leadership8 min read
AI Vendors Cannot Secure Your Enterprise Context
A provider can harden its product, but it cannot see your approvals, copied data, or tool entitlements. The enterprise still owns the exposure.
Read article →
Understand AI behavior before it becomes an incident.
Start with visibility, move to clear findings, and introduce controls only where they matter.