LangProtect: Enterprise AI
Security & Governance
Platform

Secure every AI interaction across applications, agents, and
employee workflows

Secure every AI interaction across applications, agents, and employee workflows

LangProtect provides a unified AI security and governance layer for employees, AI apps, and agent/MCP environments. It combines real-time visibility, runtime protection, intent categorization of AI usage, intent security, and policy enforcement in one enterprise-ready platform.

Its core capabilities include security from prompt injection and jailbreak defense, PII/PHI scrubbing, toxic content control, agent guardrails, RAG protection, shadow AI monitoring, and audit-ready governance.

The result is faster, safer AI adoption with stronger control, compliance readiness, and trust. LangProtect also emphasizes rapid risk detection, monitored AI tools, and broad policy coverage

AI Capabilities of LangProtect

AI Capabilities of
LangProtect

A powerful mix of AI security, policy enforcement, and governance capabilities built to protect enterprise AI usage, applications, and agentic workflows in real time.

Prompt Injection & Jailbreak Defense

Blocks prompt injection, jailbreak attempts, and malicious instruction overrides in real time across AI applications, autonomous agents, and employee AI usage.

01

PII / PHI Protection

Automatically detects, scrubs, or redacts sensitive PII and PHI data to reduce exposure risks in regulated enterprise environments.

02

Shadow AI Visibility

Provides visibility into unsanctioned AI tools, extensions, and employee usage through browser-level monitoring and governance beyond standard controls.

03

Runtime AI Application Security

Applies inline runtime protection during live AI interactions to secure prompts, outputs, context, and downstream system actions.

04

Agent & MCP Guardrails

Enforces centralized controls for agents and MCP workflows with RBAC, tool-call validation, semantic analysis, and real-time policy enforcement.

05

Audit-Ready Governance

Delivers traceability through enforcement logs, structured audit evidence, and policy-based governance across employees, AI applications, and agents.

06

Solving Complex AI Security Challenges
with LangProtect

Solving Complex AI Security Challenges with LangProtect

This AI security and governance platform addresses the toughest challenges enterprises face when scaling AI across teams, applications, and autonomous systems.

Problem

Lack of visibility into employee use of public AI tools creates major shadow AI risks.

AI Solution

LangProtect provides runtime discovery of AI tool usage, contextual policy enforcement, identity-aware governance, and audit-ready evidence to uncover and govern shadow AI activity in real time.

Problem

Production AI applications are exposed to prompt injection, jailbreaks, data leaks, and unsafe outputs.

AI Solution

LangProtect Armor applies inline runtime enforcement during live request-response cycles, scanning prompts, context, and outputs to prevent harmful behavior before it reaches business systems.

Problem

Autonomous agents and MCP-connected systems can perform high-risk actions and expose sensitive data without sufficient oversight or DLP controls.

AI Solution

LangProtect Vector introduces centralized policy control, RBAC for agents, MCP resource guardrails, semantic intent analysis, DLP enforcement, and human-readable audit logs to govern the autonomous action layer safely.

Problem

Traditional DLP security controls are not built to govern AI interactions, data movement, or autonomous behavior.

AI Solution

LangProtect turns AI governance into an operational layer with real-time monitoring, policy enforcement, telemetry integration, and defensible audit trails built for enterprise environments.

LangProtect vs Traditional AI Security Approaches

LangProtect vs Traditional AI
Security Approaches

LangProtect positions itself as a unified, real-time AI security and governance
layer, whereas traditional controls often operate too late, too generically, or without the context
needed for modern AI workflows.

Traditional Security Approaches

Limited visibility into employee AI usage outside sanctioned apps
Little or no runtime understanding of prompt semantics and model behavior
Traditional DLP scans words, data access, and movement patterns, but does not understand the meaning or intent of AI interactions
Weak controls for prompt injection, jailbreaks, hidden instructions, and intent-based misuse
Minimal oversight of agent tool calls and MCP-connected workflows
Compliance evidence is fragmented across logs, browsers, and point tools
Detection often happens after exposure, audit failure, or production issues occur

LangProtect

Unified coverage across employees, AI apps, and agents/MCP
Understands intent and contextual meaning, not just words, data patterns, or access points
Real-time protection against prompt injection, jailbreaks, unsafe outputs, and sensitive data leaks
Inline runtime enforcement for application and agent workflows
Role-aware and policy-driven control of tools, data access, and autonomous actions
Audit-ready records and governance workflows for enterprise compliance
Fast risk detection with enterprise-grade security controls and certifications

Businesses save time, improve quality, and boost visibility
when they choose WriteEasy.

Businesses save time, improve quality, and boost visibility when they choose WriteEasy.

Notable Achievements & Outcomes

LangProtect highlights measurable AI governance outcomes across protection, visibility, policy coverage, and speed, offering strong public metrics suitable for a credible portfolio page.

1L+

Prompts Detected

100+

AI Tools Monitored

20+

Policies Applied

99%

Sensitive Data Coverage

<5ms

Risk Detection

Traditional Development vs Our AI
Security Development Timeline

Traditional Development vs Our AI Security Development Timeline

Building LangProtect required rapid iteration, secure architecture planning, runtime validation, and seamless integration across employee AI usage, applications, and agent workflows.

Total: 24–32 weeks

Total: 8–12 weeks (Accelerated AI-driven
delivery approach)

Traditional AI Security
Platform Development

Phase 1
Planning & Security Architecture → 6–8 weeks
Phase 2
Core Platform Development → 10–14 weeks
Phase 3
Integration, Testing & Compliance Validation → 8–10 weeks

With Quokka Labs’ AI
Workflow

Phase 1
Accelerated Planning & Architecture → 2–3 weeks
Phase 2
Agile Security Feature Development → 4–6 weeks
Phase 3
Rapid Integration, Validation & Deployment → 2–3 weeks

VS

Total: 8–12 weeks
(Accelerated AI-driven delivery approach)

The Technologies Behind LangProtect

We used a modern combination of AI security frameworks, scalable backend services, browser-based controls, and frontend technologies to build LangProtect’s enterprise-ready protection platform.

Frontend

Built with React and Vite to deliver a modern, responsive, and efficient user interface.

Backend

Built with Python 3.12, FastAPI, Uvicorn, Pydantic, and SQLAlchemy Asyncio for scalable APIs and secure backend operations.

Scan Service

AI Protection Layer

Integrated PyTorch, Transformers, Tiktoken, and Optimum ONNX Runtime for LLM protection and runtime threat detection.

Interceptor App

Developed with Electron, React, and http-mitm-proxy to support desktop-level traffic interception and policy enforcement.

Browser Extension

Built using React, pdfjs-dist, jszip, and crypto-js for browser-level monitoring, secure processing, and content support.

AI Consulting That Engineered LangProtect

From AI security planning to runtime governance implementation, our consulting approach helped shape LangProtect into an enterprise-ready platform for protecting AI apps, employees, and agents.

Assessment

Evaluated enterprise AI risks, governance goals, and platform requirements to define LangProtect’s secure and scalable foundation.

Assessed vulnerabilities such as prompt injection, jailbreak attempts, shadow AI usage, and sensitive data leakage across enterprise AI workflows.

Mapped intent security, compliance, and policy requirements into a governance framework for real-time AI monitoring and enforcement.

Designed an extensible platform direction capable of supporting growing AI adoption, complex workflows, and enterprise-grade protection demands.

Training

Trained teams to understand and manage AI security operations with greater clarity and confidence.

Introduced key concepts around AI threats, unsafe interactions, and runtime security risks.

Helped teams align platform controls with governance privacy policy, data protection needs, and responsible AI usage standards.

Enabled practical processes for reviewing alerts, validating controls, and maintaining oversight across live AI environments.

Implementation

Delivered a phased roadmap to bring AI security, governance, and runtime protection into production.

Implemented runtime safeguards for prompts, outputs, and contextual data flows across AI-driven applications.

Rolled out policy compliance controls for agent workflows and MCP-connected systems to improve access to security and auditability.

LangProtect: Enterprise AI Security & Governance Platform

LangProtect provides a unified AI security and governance layer for employees, AI apps, and agent/MCP environments. It combines real-time visibility, runtime protection, intent categorization of AI usage, intent security, and policy enforcement in one enterprise-ready platform.

Its core capabilities include security from prompt injection and jailbreak defense, PII/PHI scrubbing, toxic content control, agent guardrails, RAG protection, shadow AI monitoring, and audit-ready governance.

The result is faster, safer AI adoption with stronger control, compliance readiness, and trust. LangProtect also emphasizes rapid risk detection, monitored AI tools, and broad policy coverage

Trusted by startups and leading brands

AI Capabilities of LangProtect

AI Capabilities of LangProtect

A powerful mix of AI security, policy enforcement, and governance capabilities built to protect enterprise AI usage, applications, and agentic workflows in real time.

Prompt Injection & Jailbreak Defense

01

PII / PHI Protection

02

Shadow AI Visibility

03

Runtime AI Application Security

04

Agent & MCP Guardrails

05

Audit-Ready Governance

06

Solving Complex AI Security Challenges with LangProtect

Solving Complex AI Security Challenges with LangProtect

Problem

AI Solution

Problem

Problem

AI Solution

Problem

LangProtect vs Traditional AI Security Approaches

LangProtect vs Traditional AI Security Approaches

LangProtect positions itself as a unified, real-time AI security and governance layer, whereas traditional controls often operate too late, too generically, or without the context needed for modern AI workflows.

Traditional Security Approaches

LangProtect

Notable Achievements & Outcomes

LangProtect highlights measurable AI governance outcomes across protection, visibility, policy coverage, and speed, offering strong public metrics suitable for a credible portfolio page.

1L+

100+

20+

99%

<5ms

Traditional Development vs Our AI Security Development Timeline

Traditional Development vs Our AI Security Development Timeline

Total: 24–32 weeks

Total: 8–12 weeks (Accelerated AI-driven delivery approach)

Traditional AI Security Platform Development

With Quokka Labs’ AI Workflow

VS

Total: 8–12 weeks (Accelerated AI-driven delivery approach)

The Technologies Behind LangProtect

Frontend

Backend

Scan Service

AI Protection Layer

Interceptor App

Browser Extension

AI Consulting That Engineered LangProtect

From AI security planning to runtime governance implementation, our consulting approach helped shape LangProtect into an enterprise-ready platform for protecting AI apps, employees, and agents.

Assessment

AI Risk Discovery

Intent-Based Governance Planning

Scalability Strategy

Training

AI Security Awareness

Policy & Protection Readiness

Monitoring Workflows

Implementation

Employee AI Monitoring

AI Application Security Layer

Agent & MCP Governance

Need expert guidance to turn your AI idea into a scalable product?

Need expert guidance to turn your AI idea into a scalable product?

Other Case Studies

AI-Writing Assistant

30%

AI Gardening Notification System

90%

AI-Powered End-to-End Web App Testing

80%

AI-Driven Lead Generation Platform

70%

LangProtect: Enterprise AI
Security & Governance
Platform

Trusted by startups and
leading brands

AI Capabilities of
LangProtect

Solving Complex AI Security Challenges
with LangProtect

LangProtect vs Traditional AI
Security Approaches

LangProtect positions itself as a unified, real-time AI security and governance
layer, whereas traditional controls often operate too late, too generically, or without the context
needed for modern AI workflows.

Traditional Development vs Our AI
Security Development Timeline

Total: 8–12 weeks (Accelerated AI-driven
delivery approach)

Traditional AI Security
Platform Development

With Quokka Labs’ AI
Workflow

Total: 8–12 weeks
(Accelerated AI-driven delivery approach)

Need expert guidance to turn your AI idea into
a scalable product?

AI-Driven Lead
Generation Platform