PH Deck

Users traditionally spend considerable time and effort creating professional portfolios manually. The process involves gathering information, designing layouts, and ensuring the final product is polished and cohesive. The drawbacks include spending excessive time on design and formatting rather than focusing on content, and the possibility of missing key information due to manual oversight.

Developers face challenges in building real-world AI applications due to complex processes and lack of practical guidance.

Users struggle with procrastination due to overwhelming tasks, leading to delayed starts and reduced productivity. Traditional time management methods lack immediacy and fail to create momentum.

Users wanting to build SaaS businesses face high costs, the need for technical expertise, and extended development times.

Developers and businesses face significant challenges and delays when trying to build AI-powered applications due to the complexity of integrating various AI building blocks and dealing with different LLMs. The complexity and time-consuming nature of creating custom AI apps, workflows, and chatbots significantly hinder productivity and innovation.

Users currently use traditional methods for portfolio creation, leading to time-consuming updates and limited customization features. The old solutions often lack the ability to offer dynamic interaction, like AI Resume Chat, and are restricted in functionality.

Many investment managers and individual investors struggle to track and optimize their investments effectively. The traditional method often involves disparate spreadsheets or basic financial tools, which can be cumbersome and lack real-time insights. This approach does not provide real-time performance tracking, asset allocation insights, or AI personalized advice.

Users struggle to manually take notes during meetings, leading to potential loss of important details and key points. Users face challenges in organizing and structuring meeting notes efficiently.

Users traditionally learn AI through online courses or bootcamps that lack hands-on project experience and personalized mentorship, resulting in limited practical skills and career readiness.

Users face time-consuming and inflexible development processes when creating AI agents, struggling with challenges in integrating various LLMs and workflows using traditional coding methods.