PH Deck

Users currently manually transcribe handwritten notes from PDFs or images, which is time-consuming and error-prone. Basic OCR tools lack summarization features, leading to inefficiency in processing and reviewing notes.

In the current situation, users struggle to extract text from images manually, which is time-consuming and prone to errors.

Users need to extract text from images, such as printed text, handwritten notes, or screenshots. The existing process can be cumbersome and often requires manual transcription, which is time-consuming and prone to errors. The drawbacks of the old situation include the difficulty to quickly and accurately find and extract desired text from various image formats and languages.

Users often struggle to scan and extract text from images efficiently, especially when dealing with documents in multiple languages.

Users struggle with extracting text from PDFs, which is time-consuming and requires additional software or tools.

Users struggle with manually extracting text from PDFs and other document images

Users need to manually extract text from images, PDFs, and presentations, leading to time-consuming and error-prone processes.

Users currently rely on various note-taking applications or paper-based solutions.

Users struggle with manual organization, inefficient retrieval, scattered notes leading to missed tasks, and potential privacy concerns when managing notes across multiple sources.

Users struggle with inconsistent text formatting across platforms and documents, leading to inefficiencies and a lack of professionalism.

Drawbacks include the time-consuming manual effort required to ensure consistent text format, potential for human error, and the inability to quickly switch between different text styles.