PH Deck

Developers and companies using Generative Pre-trained Transformers (GPTs) often struggle to track usage, performance, and user conversations effectively. This makes it challenging to optimize GPT applications for user needs and business goals.

Users often find navigating through different Android apps for various tasks complicated and time-consuming. They might not always know the best app for a specific task or the most efficient way to achieve their goals.

SaaS products often face challenges such as low user engagement, suboptimal pricing strategies, and difficulty in leveraging the latest AI technologies, which leads to decreased customer satisfaction and revenue.

Traditional approaches to achieving goals using language models require manual input and intervention at every step, leading to inefficiencies and discontinuities in the thought process.

Marketers face the challenge of staying updated with the ever-evolving digital marketing landscape due to the overwhelming amount of information across multiple sources. This makes it difficult to find and digest relevant insights quickly and efficiently.

Users struggling to manage and analyze feedback from multiple sources face issues with data scattering and lack of actionable insights.

In the context of remote meetings, users often face difficulties in distilling important information, tracking action items, and efficiently planning follow-ups, leading to decreased productivity and miscommunication. Difficulties in distilling important information, tracking action items, and efficiently planning follow-ups

Users experience inefficiencies in managing their emails, leading to time wastage, reduced productivity, compromised communication quality, and increased workload. The time wastage, reduced productivity, compromised communication, and increased workload are the drawbacks of the old situation.

Startups struggle to receive insightful feedback on pitches and find suitable investors, leading to prolonged fundraising efforts. VCs and angel investors face difficulties in performing sentiment analysis and accurately evaluating startups to make data-driven investment decisions. The drawbacks of the old situation include inadequate pitch feedback, difficulty in investor matchmaking, and the challenge of making informed investment choices.

Product teams often struggle to understand user experiences across various aspects of their products, leading to a fragmented understanding and the use of multiple tools, which complicate and increase the cost of insight gathering.