NeurAudit Sentinel

AI-powered public contract intelligence platform that detects corruption risks, monitors anomalies, and helps investigators act faster using AWS Aurora DSQL and Vercel.

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Inspiration

Public procurement corruption remains one of the biggest challenges in many countries. Auditors, investigators, and compliance teams often face an overwhelming amount of fragmented contract data, making it difficult to detect suspicious patterns early.

We built NeurAudit Sentinel to solve this problem.

Our goal was to create an AI-powered intelligence platform capable of transforming thousands of public contracts into actionable risk signals. Instead of manually reviewing large datasets, investigators can instantly identify suspicious contracts, monitor entities, and detect anomalies in real time.

We wanted to build something practical, scalable, and impactful—software that could genuinely help improve transparency and accountability in public contracting.

What it does

NeurAudit Sentinel is an AI-powered procurement intelligence platform designed to detect corruption risks and suspicious procurement activity.

The platform continuously analyzes procurement-related data and helps users:

  • Detect high-risk contracts
  • Monitor suspicious entities
  • Track procurement anomalies
  • Receive real-time alerts
  • Investigate corruption risk faster

The system assigns risk scores to contracts based on suspicious indicators such as unusual contract values, repeated vendor patterns, or abnormal procurement behavior.

This allows investigators and analysts to focus on the highest-risk cases first.

How we built it

We built NeurAudit Sentinel as a full-stack application using a modern cloud-native architecture.

Frontend

  • Next.js
  • TypeScript
  • TailwindCSS
  • Recharts

The frontend provides a clean intelligence dashboard with:

  • Risk monitoring
  • Alert visualization
  • Watchlists
  • Investigation tools

Backend

The backend was built using Next.js API routes and server-side processing for real-time data handling and risk analysis.

Main API modules include:

  • Alerts engine
  • Watchlist management
  • Monitoring pipeline
  • Investigation engine

Database & Cloud Infrastructure

A major focus of this project was building on production-grade infrastructure from day one.

We used:

  • Vercel for deployment and frontend hosting
  • AWS Aurora DSQL as our cloud database
  • PostgreSQL-compatible architecture for scalable structured data storage

Aurora DSQL enables fast, scalable, and reliable storage for:

  • Contracts
  • Alerts
  • Entities
  • Monitoring data
  • Risk signals

This architecture ensures NeurAudit Sentinel can scale from small datasets to enterprise-level workloads.

Challenges we ran into

One of the biggest challenges was designing a data architecture that balanced:

  • Real-time responsiveness
  • Scalable storage
  • Reliable querying
  • Clean frontend performance

Another challenge was building an interface that makes complex risk intelligence easy to understand.

Large volumes of contract data can easily become overwhelming, so a major design challenge was turning raw data into meaningful visual insights.

We also faced deployment and production build issues while integrating the AWS + Vercel stack, particularly around type safety, production builds, and database connectivity.

Solving these challenges significantly improved the project’s architecture and stability.

What we learned

This project taught us a lot about building production-ready full-stack applications with modern cloud infrastructure.

Key learnings included:

  • Designing scalable cloud-native architectures
  • Integrating AWS Aurora DSQL with Vercel
  • Building efficient data pipelines for monitoring systems
  • Creating dashboards for actionable intelligence

We also learned how important infrastructure decisions are when building software intended for real-world scale.

What's next for NeurAudit Sentinel

We see strong potential for NeurAudit Sentinel to evolve into a commercial B2B platform for:

  • Government agencies
  • Auditing teams
  • Compliance firms
  • Investigative organizations

Future features include:

  • Live public procurement integrations
  • Advanced AI anomaly detection
  • Predictive risk scoring
  • Automated reporting
  • Multi-region monitoring

Our vision is to build a powerful intelligence platform that helps detect corruption before damage happens.

Built With

  • ai
  • analytics
  • api
  • architecture
  • aurora
  • cloud
  • computingamazon
  • css
  • data
  • dsql
  • full-stack
  • learning
  • machine
  • next.js
  • node.js
  • postgresql
  • react
  • recharts
  • rest
  • risk
  • sdk
  • serverless
  • tailwind
  • typescript
  • vercel
  • visualization
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