Case study
Revolutionizing grain
quality assessment with
AI-driven mobile app

Our client needed an AI-backed real-time quality testing application for checking their agri-produce.

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Challenges
Our client, a major agri-business player, struggled with time-consuming and error-prone quality assessments. Manual methods took 3 days, causing bottlenecks.
Solution
We developed an AI-powered mobile app, automating grain quality assessment with computer vision and AI/ML algorithms.
Outcomes
  • 3-day process reduced to 3 seconds
  • Cost efficiency
  • Empowered farmers
  • 90% accuracy
  • Enhanced transparency
Tech stack
Next JS, MongoDB, Node JS, Kotlin, Android Studio, Swift, Docker, Python, AWS, DevOps.
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