Understand AI use
See how employees, assistants, and agentic tools are actually using AI.
Solutions
AI governance is a runtime control problem, not a procurement problem. AI usage is a company policy decision, not a vendor-default decision, and 3LS helps teams see, decide, and enforce before behavior crosses a line.
See how employees, assistants, and agentic tools are actually using AI.
Spot PII, secrets, and risky interactions before a prompt is sent, a file is uploaded, or an agent delegates work to a tool.
Choose when to allow, warn, or block and give teams evidence for every decision.
Solutions
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
See whether AI is being used for drafting, coding, research, summarization, data handling, or tool-driven work.
Explore capabilityPII detection
Surface personal information, credentials, and restricted content inside prompts, tool inputs, and outputs.
Explore capabilityAI controls
Apply allow, warn, and block decisions based on context so teams can guide AI use without slowing everyone down.
Explore capabilityOperator view
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
Outcome
Give operators a clear picture of where AI is helping, where it is handling data, and where closer review is needed.
Capability
Detect risky content and suspicious AI behavior before it becomes a data exposure or a control failure.
Control
Apply allow, warn, and block outcomes that make sense to both security teams and the people using AI every day.
From the blog
Articles mapped to the same themes as the solutions catalog: visibility, classification, sensitive-data handling, and action-oriented controls.

After an AI exposure, the hardest question is usually what your organization cannot answer: where AI is active, what was pasted in, and what was shared. That visibility gap turns shadow AI into an incident multiplier.

A single paste can become a breach. From Samsung's ChatGPT incident to training data extraction, 26% of organizations are feeding sensitive data to public AI.

Microsoft is adding native AI controls while OpenAI is turning ChatGPT into a shared agent workspace. Both trends point to the same requirement: one runtime governance layer across prompts, files, memory, tools, and actions.