Inspiration

The rapid rise of generative AI (GenAI) has transformed industries, offering incredible opportunities for innovation and efficiency. However, it also brings significant risks—security breaches, regulatory violations, and ethical concerns—that enterprises can’t ignore. We were inspired to create AegisAI by the growing need for a robust governance system that ensures AI interactions are secure, compliant, and trustworthy. High-profile AI missteps, evolving regulations like the EU AI Act, and the increasing reliance on AI in business settings drove us to build a "guardian" for enterprise AI, empowering organizations to harness GenAI’s potential without compromising safety or trust.

What it does

AegisAI is a multi-agent governance system designed to monitor, regulate, and audit GenAI applications in real time. It features seven specialized agents working together to secure every step of the AI interaction process:

Prompt Guard: Scans prompts for PII, harmful content, or regulatory risks. Policy Enforcer: Applies dynamic, role-based rules and organizational policies. LLM Processor: Processes approved prompts securely via AWS Bedrock or other LLMs. Output Auditor: Checks responses for toxicity, bias, or hallucinations. Audit Logger: Records all interactions for traceability and compliance. Advisory Agent: Explains governance decisions in natural language. Feedback Agent: Gathers user feedback to improve the system. AegisAI also includes a GenAI Use Cases Hub, showcasing practical applications like AI-Driven Live Call Insights and Smart Synthetic Data Generation, proving its value across industries.

How we built it

We designed AegisAI with a modern, cloud-native tech stack to ensure scalability, security, and seamless integration:

Frontend: Built with React 18 and TypeScript for a responsive, type-safe UI, styled with Tailwind CSS, animated with Framer Motion, and enhanced with Recharts for data visualizations. Backend: Powered by FastAPI for fast, efficient APIs, paired with AWS Bedrock for LLM processing and AWS Lambda for serverless compute. Governance Engine: A custom multi-agent system written in TypeScript, handling real-time policy evaluation and processing. Data & Storage: Uses AWS S3 for audit logs, DynamoDB for state management, and CloudWatch for monitoring. Security: Features JWT-based authentication, AWS KMS for encryption, and IAM roles for access control. We also integrated WebSockets for real-time updates and AWS Cognito for enterprise-grade SSO, delivering a secure and user-friendly experience.

Challenges we ran into

Building AegisAI wasn’t without hurdles:

Regulatory Complexity: Adapting to diverse frameworks like GDPR and the EU AI Act required extensive research and flexible policy design. Real-Time Performance: Achieving sub-second governance decisions while maintaining accuracy demanded heavy optimization and reliance on AWS’s scalable infrastructure. LLM Integration: Securely connecting to AWS Bedrock and supporting multiple LLM models (e.g., Claude, Titan) involved intricate API management and fallback strategies. User Experience: Crafting an intuitive interface for complex tasks like policy creation and audit analysis took multiple design iterations and user feedback loops. Accomplishments that we're proud of Enterprise-Ready: AegisAI offers role-based access, full auditing, and compliance with major regulations, making it production-ready. Innovative Use Cases: Our GenAI Use Cases Hub highlights real-world applications, from call insights to synthetic data generation. Performance: End-to-end processing times under 3 seconds, with agents operating in milliseconds. Dual Appeal: Open-source components for the community and enterprise-grade features for businesses.

What we learned

This project taught us:

AI Governance: How to secure and regulate AI in enterprise settings. Cloud Development: Best practices for scalable, secure AWS-based applications. Compliance: Designing systems that meet diverse legal and ethical standards. Design: Balancing complexity and usability in enterprise software. What's next for AegisAI - Enterprise GenAI Governance System Looking ahead, we plan to:

Add advanced ML models for bias detection and anomaly scoring. Expand to multi-language support for global markets. Launch a mobile app for on-the-go monitoring. Implement federated learning for privacy-preserving training. Integrate blockchain for immutable audit trails. We’re committed to making AegisAI the go-to solution for secure, compliant, and trustworthy enterprise AI.

Built With

  • aws-bedrock-api
  • cloudwatch
  • docker
  • dynamodb
  • fastapi-platforms:-aws-(bedrock
  • framer-motion
  • github
  • iam)-apis:-openai-api
  • kms
  • lambda
  • languages:-typescript
  • lucide-react-tools:-vite
  • python-frameworks:-react
  • recharts
  • s3
  • web-speech-api-libraries:-tailwind-css
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