Overview
On-device Hindi OCR app — accurate Devanagari text recognition without internet
A fully offline mobile application that converts images of Hindi text into editable digital content — built with Flutter, Google ML Kit, and TensorFlow Lite to handle complex Devanagari script ligatures without internet.
Published on Google Play with positive reviews highlighting accuracy on handwritten and printed text.
100%Offline Processing
0Cloud Dependency
IndiaPrimary Market
HighDevanagari Accuracy
Services Provided
Flutter App Development, ML Model Integration, App Store Publishing
Technology Stack
Flutter, Google ML Kit, TensorFlow Lite, Dart
Timeline
8 Weeks
Key Features
On-device Devanagari OCR recognition, No internet connection required, Copy extracted text to clipboard, Share extracted text to other apps, Batch image processing, Accurate handling of complex Hindi ligatures
Outcome
Published on Google Play with positive reviews highlighting accuracy on handwritten and printed text.
Process
Challenge & Solution
The Challenge
No reliable offline OCR for the Hindi language
Most OCR tools require internet connectivity or fail to accurately handle the complex conjunct consonants and ligatures of Devanagari script.
- → All major OCR apps requiring cloud processing
- → Poor Devanagari accuracy in general-purpose OCR tools
- → Data privacy concerns with cloud-based document recognition
- → No lightweight solution for basic Hindi text extraction
The Solution
Production-grade Hindi OCR that runs entirely on your phone
Adam Apps integrated Google ML Kit with a TensorFlow Lite model fine-tuned for Devanagari script — the entire pipeline runs on-device in milliseconds.
- → Google ML Kit text recognition for Devanagari base layer
- → TensorFlow Lite model for complex conjunct character handling
- → Full offline capability — processes on-device instantly
- → Clean Flutter UI with one-tap copy and share functionality
Next Project
Xpensly
app