Discover the estate
Discover observed AI products, provider accounts, MCP installations and tool revisions.
Runtime AI Governance with inventory, gateway controls, approvals, cases, and evidence.
See AI use. Apply policy. Keep the evidence.
3LS brings AI and MCP inventory, gateway controls, policy approvals, cases and audit evidence into one platform. Discover observed AI use, control supported AI and tool workflows, and give operators evidence to review and respond.
- Discover the estate
- Observed AI and MCP
- Control supported workflows
- Policy and approvals
- Respond with evidence
- Cases and audit records
Visibility:
On-device collection brings supported AI activity into view for classification and policy evaluation.
Policy ownership:
Your organisation owns the policy evaluation and the resulting evidence.
Control supported workflows
Apply configured policy on supported traffic routed through the gateway and supported browser and managed MCP paths.
Respond with evidence
Assign case owners, retain remediation evidence and review attributable decisions.
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 how organisational policy applies.
Phase 1
then
AI activity is observed
Available evidence shows where a user, assistant, OAuth app, or tool is using AI.
Phase 2
then
Purpose is classified
3LS classifies what the interaction appears to be for and how the AI is being used.
Phase 3
then
Risk evidence is surfaced
Sensitive content and risky behaviour are surfaced for evaluation.
Phase 4
Policy is evaluated
Teams evaluate the available context and risk against organisational policy, then retain the result.
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. Policy evaluation answers what the available evidence means.
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
Policy evaluation
What does policy say?
Evaluate the available context against organisational policy and keep the reasoning operators need to review.
Outcome: Explainable policy evaluation
Illustrative operator view
Turn AI interactions into clear decisions
Give security teams a readable trail of what was detected, how policy was evaluated, and which evidence supported the result.
Illustrative findings
Activity class, sensitivity, and policy evaluation
3 evaluations captured
Activity
Activity class
Sensitivity
Policy result
Customer records pasted into an assistant
Data handling
PII detected
Needs review
Prompt requests external tool access
Tool use
No sensitive data
Within policy
Prompt includes an API token and a request to share it
Data sharing
Secret detected
Escalate
Solutions
Go deeper on the capabilities behind the story.
Explore the five capability groups in the 3LS Platform, from inventory and governed access to operator response and evidence.
AI and MCP Inventory
Know the observed estate
Discover observed AI products, provider accounts, MCP installations and tool revisions. Track ownership, provenance and observation freshness.
Explore capabilityAI Gateway Controls
Control access to models and tools
Apply policy to approved providers, models and tool groups. Inspect selected text and control usage on supported traffic routed through the gateway.
Explore capabilityPolicy and Approvals
Publish policy and handle exceptions
Validate and publish signed policies, track their application, and manage scoped exceptions with approval and expiry.
Explore capabilityRisk and Response
Give findings a path to resolution
Prioritise findings, assign case owners and retain evidence of remediation.
Explore capabilityGovernance Evidence
Review decisions and export inventory
Review attributable policy decisions, activity and case history. Export observed inventory for governance and assurance reviews.
Explore capabilityAI Gateway / 3LS Platform
Govern the request and the protected response.
Four capabilities work on supported gateway paths, from selected prompts and eligible models to usage controls and tool proposals before harness delivery.
Tool security before the harness →
Check model-proposed tool calls and selected arguments before release to the client runtime on configured protected response paths.
Prompt classification →
Use selected-text topic/activity labels and separate risk signals in configured policy decisions.
Model routing →
Select among approved, eligible models using policy, configured classification outcomes and permitted user or session choices.
Cost control →
Review attributable usage and cost, request-rate controls and eventual monthly thresholds with reporting freshness.
Compliance and Assurance
Connect governance questions to product evidence.
Use inventory, signed policies, approvals, activity and remediation records to support governance reviews. Combine product records with organisational assessments, policy, competence and supplier diligence.
Map your governance questions to product evidence →From 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 Security Risk and the Shadow Database Problem
AI chat feels private to users, but providers and operators control storage, sharing, indexing, and transcript exposure. That makes chat security a governance and data-exposure problem.
Read article →
Thought Leadership8 min read
The Enterprise AI Visibility Gap Behind Shadow AI Risk
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.
Read article →
Thought Leadership9 min read
Workspace Features Create New Enterprise Data Paths
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.
Read article →
Understand AI behavior before it becomes an incident.
Start with visibility, move to clear findings, and introduce controls only where they matter.