Rifki Rosada | Public Android + AI

OffScan AI

Built and shipped an offline OCR Android app focused on privacy-preserving, on-device text extraction.

Android Product Engineer 6-week build and release Public product build
  • Problem

    Users needed OCR extraction with stronger privacy guarantees and no network dependency.

  • My scope

    Designed an offline-first OCR flow for camera capture and image import.

  • Result

    Published an Android workflow that performs OCR locally without cloud upload requirements.

Problem

Users needed OCR extraction with stronger privacy guarantees and no network dependency.

Constraints

  • All processing needed to stay on-device
  • UX had to support quick single-hand capture flow
  • Performance and battery impact needed careful balance

Delivery

  • Designed an offline-first OCR flow for camera capture and image import.
  • Implemented on-device processing and result export interactions.
  • Published support and policy pages so the product could ship with the right operational basics.

Result

  • Delivered a privacy-first OCR experience for Android users.
  • Enabled reliable text extraction without mandatory internet access.
  • Packaged the app with supporting product infrastructure instead of a prototype-only handoff.

Tech stack

  • Android
  • On-device OCR
  • Edge AI
  • Mobile Product

Related delivery proof across internal tools, automation, Android + AI, and supporting product systems.

Android + AI

Client delivery

Media Android App - AI Chat + Search UX

Android AI UX Engineer3-week delivery sprint

Made the AI-assisted discovery flow clearer and more reliable from chat prompt to search result.

  • Problem

    Users lacked a clear transition from AI chat prompts to meaningful search actions, and state sync issues reduced UX reliability.

  • My scope

    Worked inside the existing WebView-based AI entry path so the feature fit the live app architecture.

  • Result

    Made the AI-assisted discovery flow clearer and more reliable from chat prompt to search result.

  • Android
  • Kotlin
  • WebView
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Public Android + AI

Public build

I-ScanTea

ML Prototype Engineer5-week prototype

Demonstrated an on-device classification workflow for field capture scenarios.

  • Problem

    Manual quality checks required repeated visual comparison and lacked a fast digital workflow.

  • My scope

    Prepared the dataset and labeling workflow for the target classes.

  • Result

    Demonstrated an on-device classification workflow for field capture scenarios.

  • TensorFlow Lite
  • Android
  • Python
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Public Android + AI

Public build

Scanberry

Mobile Computer Vision Engineer4-week prototype

Validated a practical on-device scan flow for classification without cloud dependency.

  • Problem

    The workflow needed rapid classification support in environments with unstable connectivity.

  • My scope

    Built a lightweight model iteration and evaluation loop.

  • Result

    Validated a practical on-device scan flow for classification without cloud dependency.

  • Computer Vision
  • Android
  • TensorFlow Lite
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