Lumia Security

What Lumia Security does

Lumia Security offers an AI Usage Control platform designed to secure and govern the use of AI and autonomous agents within enterprises. Operating at the network layer, Lumia provides full visibility and enforcement over how employees and AI agents interact with AI systems. The platform establishes governance aligned with business policies, security standards, and regulations. Powered by its proprietary Protocol Analysis Engine, Lumia analyzes AI-powered applications and agent actions to assess risk and ensure safe AI usage by default. It unifies governance, visibility, and control across every layer of AI adoption, offering solutions from discovery to enforcement. Lumia's approach focuses on understanding content, context, and intent to enforce AI usage policies without disrupting productivity or user experience. It integrates with existing corporate IT infrastructure to analyze browser, native-app, and operating system traffic for AI interactions, extracting prompts, responses, agent actions, and metadata. The platform uses advanced LLM and SLM technology for topic analysis and classification, enabling real-time blocking, redaction, or logging of interactions.

Products

• Lumia's AI Usage Control platformA comprehensive platform that unifies governance, visibility, and control across every layer of AI adoption, from discovery to enforcement, operating at the network layer.
• Shadow AI AnalysisA solution to analyze how AI is actually used, diving into the content itself, and providing full visibility to assess AI risk exposure.
• Leakage and oversharing preventionA feature to protect sensitive information from being exposed through AI interactions.
• Maintaining ComplianceA feature to ensure AI usage stays aligned with organizational policies, security frameworks, and evolving privacy and regulatory requirements.
• Agent GuardrailsA solution to control how autonomous agents act on behalf of employees and systems, making every action visible, controlled, and auditable.
• AI Coding Assistant Security SolutionA solution to govern what actions coding assistants can take and inspect context in real time, preventing unsafe changes and protecting sensitive data.
• MCP Security & VisibilityA solution to control how LLMs use Model Context Protocols (MCP) to access tools, data, and systems, providing continuous visibility and real-time policy enforcement.

Key capabilities

• Network layer operation for full visibility and enforcement
• Proprietary Protocol Analysis Engine for deep and contextual analysis
• Shadow AI detection and inventory of AI services and agents
• Topic analysis using natural language definitions for business-specific risk tracking
• AI-Risk Exposure assessment based on context and risk factors
• User identification and role-based oversight for AI usage
• Real-time enforcement of AI usage policies based on content, context, and intent
• Deep Packet Inspection for visibility into AI service, content, and topics/intent
• Advanced LLM and SLM technology for classification and detection
• Integration with existing corporate IT infrastructure
• Prevention of leakage and oversharing of sensitive information
• Maintenance of compliance with policies, security frameworks, and regulations
• Guardrails for autonomous agents, including visibility, controlled actions, adversarial protection, and auditing
• Security for AI coding assistants, including visibility, context inspection, access controls, and policy enforcement
• MCP discovery, integration mapping, context inspection, and policy enforcement for LLM interactions with tools and systems
• Ability to block, redact, or log AI interactions
• Open-by-default approach to AI usage with safe controls
• Adversarial defense against prompt injection, model confusion, and external manipulation for agents
• Continuous recording of agentic behavior for audit trails and compliance

Use cases

• Securing and controlling employee usage of AI across the organization
• Governing autonomous agent actions
• Analyzing shadow AI usage and assessing risk exposure
• Preventing sensitive information leakage and oversharing through AI interactions
• Ensuring AI usage compliance with organizational policies, security frameworks, and regulations
• Controlling actions of autonomous agents
• Securing AI coding assistants working with sensitive code and credentials
• Governing LLM interactions with Model Context Protocols (MCP) for tool access and system operations
• Defining and enforcing business-specific topics for monitoring AI interactions
• Managing AI risk based on user roles and departments
• Applying out-of-the-box controls for GDPR, HIPAA, PCI, TPRM
• Preventing employees from consuming or exposing unsafe information via AI
• Stopping AI from generating malicious code or content
• Tracking agent actions, permissions, and affected systems
• Defining approved and delegated autonomous actions for agents
• Detecting and neutralizing malicious or unintended agent behavior
• Auditing and ensuring accountability for agent actions

AI approach

Lumia Security provides an AI Usage Control platform that operates at the network layer to offer visibility, governance, and real-time guardrails for AI interactions. It uses a proprietary Protocol Analysis Engine to analyze AI-powered applications and agent actions, assessing risk and ensuring safe AI usage. The platform leverages advanced LLM and SLM technology for topic analysis and classification, enabling business-specific enforcement policies based on content, context, and intent across various modalities like text, file, voice, and visual data.

Tech named: Protocol Analysis Engine, LLM, SLM, Deep Packet Inspection

Industries served

• Computer and Network Security
• Law Firms

What it says sets it apart

• Operates at the network layer for full visibility and enforcement
• Proprietary Protocol Analysis Engine capable of analyzing thousands of AI-powered applications
• Deep and contextual analysis of AI interactions
• Uses advanced LLM and SLM technology for classification and detection without relying on tagging or labeling data
• Integrates with existing corporate IT infrastructure without disruption to productivity or user experience
• Focuses on content, context, and intent for policy enforcement, rather than just domains or app lists
• Provides comprehensive platform unifying governance, visibility, and control across all layers of AI adoption
• Enables open-by-default AI usage while maintaining control
• No MCP Gateway required for MCP discovery and control

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.