AI-based quality checking: Developed the QC module that uses computer vision and AI/ML algorithms to detect and classify grains, ensuring high accuracy.

Custom quality standards: Users can create quality standards for different commodities and variants, adding required quality parameters.

Instant report generation: The app generates instant quality reports in PDF or other formats.

Commodity trading and Listing: Designed modules for commodity trading and listing agriculture products and services.

High availability and security: Implemented high-availability solutions with load balancers, auto-scaling, and Kubernetes orchestration for security.

Efficient development: Utilized Azure DevOps and Git Flow branching strategy for faster product development and delivery.

Database Integration: Integrated the app with the client's database and middleware for efficient data management.

99% efficiency improvement: On-the-spot assessment reports within 3-4 seconds, saving time and eliminating the need for additional resources.

Enhanced user experience: Local language support, offline functionality, and minimal environment requirements.

Expanded market reach: Farmers and businesses reached a larger audience, expanding their potential market and getting better prices.

Real-time accessibility: Users can access information and updates in real-time, enabling better decision-making.

Faster software shipping: Easy scaling and containerization technologies freed up DevOps teams for innovation.

Cost savings: Saved 20% of costs on resources with effective scaling on AWS.

Quality improvement: Reduced time and cost associated with quality checking, ensuring regular quality checks and 90% accuracy compared to lab data.