PH Deck

Users often struggle with creating and managing AI prompts effectively, leading to repetitive copying and pasting from notes, which is inefficient and time-consuming.

Users struggle to craft effective, optimized prompts for AI models like ChatGPT, leading to time-consuming iterations and suboptimal results.

Traditional prompt engineering is complex and inaccessible for those without significant AI experience, making it challenging for users to effectively interact with large language models (LLMs) to obtain useful responses. The complexity and inaccessibility of traditional prompt engineering are the main drawbacks.

Users need to convert images or content into PDF format quickly and without saving them separately, causing hassle and wasting time.

Users manage AI prompts manually across multiple models and frameworks, leading to inefficient scaling, lack of version control, and collaboration challenges.

Users manually tweaking prompts and lack expertise in Prompt Engineering best practices, leading to inefficient and suboptimal AI outputs

Art creators struggle to come up with diverse and high-quality prompts for their artwork, leading to creative blocks and a time-consuming process.

Users struggle with inefficient prompt engineering workflows and lack a deep understanding of their Large Language Models (LLMs), which leads to suboptimal utilization of these models.

Mumbai University engineering students rely on scattered, unverified study materials and past papers, leading to inefficient preparation, time-consuming research, and risk of outdated/incomplete content.

Users struggle with inefficient and inconsistent manual methods for creating AI prompts, leading to suboptimal performance and time wastage.