Current AI code generation tools (like Cursor, GitHub Copilot) operate without awareness of organization-specific security policies, compliance frameworks, or architectural standards. This creates a critical gap where:

Generated code may violate company security requirements (data handling, authentication patterns, API usage) Compliance violations go undetected until manual review (SOC2, HIPAA, PCI-DSS standards) Developers must manually verify every suggestion against internal guidelines Security debt accumulates as non-compliant patterns proliferate across codebases

Core Issue: AI tools lack contextual understanding of enterprise constraints, making them productivity aids rather than trusted development partners.

Multiagent systems suffer from fundamental analysis and debugging challenges that make production deployment risky:

Runtime Opacity: Failures cascade through agent interactions with unclear root causes Orchestration Complexity: Agent coordination failures are difficult to trace and reproduce State Management: Distributed state across agents makes system behavior unpredictable Error Attribution: Determining which agent or interaction caused system failure is nearly impossible

Core Issue: The emergent complexity of agent interactions creates a "black box" effect where system behavior becomes unanalyzable and unreliable at scale.

LlamaCompass is an intelligent governance platform that embeds enterprise security policies and compliance frameworks directly into AI-powered development workflows while providing real-time observability for multiagent system interactions. Built on Llama's advanced reasoning capabilities, the platform continuously monitors code generation from tools like Cursor against organization-specific security requirements, automatically flagging violations and suggesting compliant alternatives before code reaches production. Simultaneously, LlamaCompass provides comprehensive visibility into multiagent system behavior through intelligent trace analysis, agent interaction mapping, and predictive failure detection—transforming opaque agent orchestrations into transparent, debuggable workflows. By combining proactive security governance with deep multiagent observability, LlamaCompass bridges the gap between AI productivity tools and enterprise reliability requirements, enabling organizations to confidently deploy both AI-generated code and complex agent systems at scale while maintaining security posture and operational visibility.

🔧 Custom Llama Fine-tuning Fine-tune Llama models using curated company-specific security policies, compliance frameworks, and organizational coding standards

🔄 Synthetic Data Generation Deploy Llama Synthetic Data Generator to create comprehensive training datasets covering diverse security scenarios and compliance edge cases

🔍 Repository Security Scanning Continuously scan both private and public GitHub repositories to identify compliance violations, security vulnerabilities, and policy deviations

⚡ Automated Remediation Planning Generate detailed remediation strategies with prioritized action items, code suggestions, and compliance pathways for identified issues

📊 Agentic System Performance Assessment Monitor, analyze, and optimize multiagent system interactions through intelligent trace analysis and behavioral pattern recognition

🔒 Security & Compliance Intelligence Hub Leverage scan-generated knowledge bases to identify security vulnerabilities, assess multiagent system risks, and ensure regulatory compliance through automated threat detection and policy enforcement monitoring

• Llama-4-Maverick-17B-128E-Instruct-FP8 - Base Model used
• Llama Synethic Data Generator Toolkit
• Llama API

• FastAPI - High-performance API framework
• Uvicorn - ASGI server for FastAPI
• Pydantic - Data validation and serialization
• CrewAI - Agentic Orchestration
• Traces - For agentic system performance

• VITE
• React JS
• Shadcn
• Bootstrap

• Ananya Gangavarupu - Github
• Srisurya Chandramouli - Github
• Deeksha Sinha - Github
• Kal Chakra - Github

1. Cloning Repo

   git clone https://github.com/anigasan/LlamaCompass
   cd LlamaCompass

2. Backend

   cd backend
   python main.py

3. Frontend

   cd frontend
   npm install
   npm run dev