LangProtect vs Quilr AI
Compare LangProtect and Quilr AI across AI security, workforce AI governance, runtime protection, deployment, integrations, and enterprise capabilities to find the right platform for your organization.
How They Differ
Compare their approaches to securing AI applications, agents, and workforce AI.
LangProtect
Enterprise AI Security Platform
Unifies AI security, governance, and visibility across applications, agents, and workforce AI.
Quilr AI
Workforce AI Security Platform
Governs employee AI usage with browser-based controls, monitoring, and policy enforcement.
Who Should Choose Which?
While both LangProtect and Quilr AI help organizations secure AI adoption, they address different parts of the AI security lifecycle.
Choose LangProtect if
- You need a unified platform to secure both AI applications and employee AI usage.
- You build and deploy custom AI applications, copilots, or AI agents that require runtime protection against prompt injection, jailbreaks, sensitive data leakage, and other AI-specific threats.
- You want centralized AI governance with customizable security policies, compliance controls, analytics, and visibility across your entire AI ecosystem from a single platform.
Choose Quilr AI if
- Your primary objective is governing how employees use generative AI tools such as ChatGPT, Claude, Gemini, and Microsoft Copilot.
- You prefer a browser-first deployment focused on AI usage visibility, policy enforcement, and employee awareness without securing custom AI applications.
Choose Both if
- Your organization needs comprehensive runtime protection for AI applications alongside dedicated workforce AI governance for employees using third-party AI tools. The two platforms can complement each other depending on your security strategy.
What Each Platform Does
Both LangProtect and Quilr AI help organizations secure AI adoption, but they take different approaches.
| Capability | LangProtect | Quilr AI | Advantage |
|---|---|---|---|
| Runtime AI Security | Native runtime AI firewall protecting prompts, responses, and AI agents | Runtime enforcement through LLM Gateway and Decision Engine | Tie |
| Prompt Injection Protection | 30+ AI security scanners with prompt injection detection | Prompt injection detection and inline sanitization | Tie |
| Hidden Prompt / Indirect Prompt Detection | Dedicated hidden prompt detection | Covered as part of runtime inspection, but not positioned as a dedicated capability | LangProtect |
| Sensitive Data Protection | PII, PHI, secrets, custom entities, policy-driven controls | Context-aware DLP with redaction and enforcement | Tie |
| Custom Security Scanners | 30+ built-in scanners + Custom Scanner Builder | Policy-driven detection, but no publicly documented custom scanner framework | LangProtect |
| AI Agent Security | Native protection for AI agents and workflows | Guardian Agents secure AI agents at runtime | Tie |
| Shadow AI Discovery | Enterprise-wide Shadow AI discovery | AI-SPM discovers AI agents, copilots, browsers, endpoints, and MCP servers | Tie |
| Policy Management | Centralized enterprise policy engine | Guardian-based policies distributed across platform components | LangProtect |
| AI Security Testing | Interactive security playgrounds for validating prompts and policies | Continuous autonomous Red Team Agents | Quilr AI |
What It Takes to Deploy Them
LangProtect and Quilr AI both protect enterprise AI, but their deployment models differ.
LangProtect
Unified AI security platform with integrated runtime protection, workforce AI governance, AI agent security, and policy management. Browser extension, desktop application, APIs, and centralized management are built into a single platform.
Quilr AI
Modular AI security platform consisting of the Decision Engine, LLM Gateway, MCP Gateway, Guardian Agents, AI-SPM, Browser Extension, and Endpoint Agent that can be deployed together or individually.
TIME TO FIRST VALUE
Hours
Days to Weeks (depending on deployment architecture and enabled components)
WHAT IT MUST CHANGE
- Deploy the LangProtect browser extension and/or desktop application.
- Connect AI applications through the AI Firewall or APIs.
- Configure organization-wide security policies from a centralized console.
- Deploy one or more platform components (LLM Gateway, Browser Extension, Endpoint Agent, MCP Gateway, Guardian Agents).
- Configure routing through the Decision Engine.
- Define policies across the deployed modules.
PREREQUISITES
- Identity provider (SSO)
- AI application or browser deployment
- Administrator access for policy configuration
- Identity provider (SSO)
- Browser or endpoint deployment
- LLM Gateway integration for AI applications
- MCP Gateway deployment (if securing AI agents)
- Configuration of Guardian Agents and Decision Engine
What Your Security Review Will Ask
Here's how LangProtect and Quilr AI compare across some of the most common enterprise evaluation criteria.
| Evaluation Criteria | LangProtect | Quilr AI |
|---|---|---|
| AI security platform | Yes | Yes |
| Runtime AI protection | Yes | Yes |
| AI agent security | Yes | Yes |
| Workforce AI security | Yes | Yes |
| AI governance & visibility | Yes | Yes |
| Custom AI security scanners | Yes | No |
| Industry-specific AI security controls | Yes | No |
| Unified AI Firewall | Yes | No |
Frequently Asked Questions
Secure Your AI Stack With Confidence
Bring runtime protection, AI governance, and workforce security together with LangProtect.
