PH Deck

Users struggle with manually converting web content to Markdown when preparing data for LLMs like ChatGPT, leading to time-consuming formatting errors and reduced workflow efficiency.

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.

Users currently need to convert PDF files into formats suitable for text processing, especially for use with LLMs.

Users face difficulty in converting ChatGPT responses to Google Docs or MS Word without losing formatting such as rich text, images, tables, and colors

Users manually convert various file formats (Word, Excel, PDF, etc.) to Markdown for AI/LLM applications, facing time-consuming, error-prone processes and lack of AI-optimized formatting.

Users need to manually extract text from images, which is time-consuming and prone to errors due to manual transcription efforts and potential inaccuracies.

Users currently face the issue of converting and saving their ChatGPT conversations manually into various files, which can be tedious and time-consuming. The drawback is the need to manually copy, format, and save the content into the desired format.

Users manually convert Markdown to DOCX/Google Docs, which is time-consuming and prone to formatting errors (e.g., broken headings, lists, or tables).

Users want to transcribe audio, video and speech into text efficiently. The old solution involves manual transcription which is time-consuming and error-prone. The drawbacks include the need to 'manually transcribe lengthy recordings' which can lead to inaccuracies and inefficiencies.

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