SentinelX- AI powered cyber security command center

Inspiration

Cybersecurity teams are overwhelmed by thousands of security alerts every day, making it difficult to identify which threats require immediate attention. Most existing solutions focus on detecting attacks after they occur. We wanted to build a platform that predicts how attacks could evolve, helping organizations take preventive action before significant damage is done.

What it does

SentinelX is an AI-powered cybersecurity command center that analyzes security incidents, predicts possible attack chains, forecasts organizational risk, and generates actionable security recommendations. It also includes an AI Security Copilot for cybersecurity assistance and a What-If Simulator that shows how security measures like MFA or network segmentation can reduce future risk.

How we built it

We built SentinelX using Next.js, React, TypeScript, Tailwind CSS, and shadcn/ui for the frontend, deployed on Vercel. The backend uses Next.js API Routes, Amazon DynamoDB for storing analyses and predictions, Amazon S3 for uploaded files, and Google Gemini AI for threat analysis, attack prediction, risk forecasting, recommendations, and the AI copilot. Data visualizations were created using Recharts, with secure cloud integration through AWS services.

Challenges we ran into

The biggest challenge was integrating AI into multiple cybersecurity workflows while ensuring consistent and structured outputs for every module. We also faced issues with cloud configuration, API authentication, prompt engineering, and designing an architecture that connects AI services, AWS resources, and the frontend into a seamless user experience.

Accomplishments that we're proud of Built an end-to-end AI-powered cybersecurity platform. Successfully integrated AI across six intelligent modules. Implemented a cloud-based architecture using AWS and Vercel. Developed interactive dashboards with real-time risk visualization. Created a predictive approach to cybersecurity instead of traditional reactive monitoring. What we learned

This project gave us hands-on experience with full-stack development, cloud-native application design, AI integration, prompt engineering, API development, AWS services such as DynamoDB and S3, and deploying scalable applications on Vercel. We also learned how AI can be applied to solve real-world cybersecurity challenges.

What's next for SentinelX – AI Powered Cyber Security Command Center

Our future roadmap includes real-time SIEM integration, MITRE ATT&CK mapping, live threat intelligence feeds, automated incident response, role-based dashboards for SOC teams, advanced attack graph visualization, historical trend analysis, compliance reporting, and support for multiple AI models to make SentinelX a comprehensive enterprise cybersecurity platform.