PH Deck

Developers and companies face challenges in managing diverse databases across multiple devices due to the necessity of building separate APIs for each setup. This process is time-consuming and expensive, making it difficult to adapt to changing database needs without significant codebase modifications.

Developers face challenges in utilizing APIs from various apps due to complexities like handling OAuth flows, token rotation, security, and access controls, leading to increased development time and complexity.

Users attempting to scrape data from the web often encounter challenges with proxies, CAPTCHAs, headers, and utilizing headless browsers, which makes data extraction cumbersome and sometimes impossible.

Users struggle with traditional app development processes that involve time-consuming coding, multiple iterations, and deployment challenges.

Developers often struggle to efficiently build interactive, real-time data apps due to the complexity of pulling data from multiple sources like APIs, databases, and event streams, and the challenges involved in creating engaging UIs and data visualizations. The complexity of integrating multiple data sources and creating interactive user interfaces significantly slows down development.

Current situation with the old solution involves developers and businesses struggling to access and integrate various datasets and APIs efficiently.

The drawbacks of the old situation include the difficulty for developers to locate and leverage high-quality APIs and structured datasets efficiently.

Users often struggle to organize and manipulate data effectively for app development, leading to inefficient processes and a reliance on complex coding skills or expensive development resources. The inefficient processes and reliance on complex coding skills are significant drawbacks.

Users often struggle with accessing and utilizing real-time news and web content data, especially when seeking structured and contextual information. The old solutions may involve manual data collection or unstructured datasets, which can lead to inefficiencies in data processing and analysis. Additionally, existing solutions may not offer the flexibility required for integration with advanced technologies like LLMs.

Developers and businesses face challenges in differentiating their AI applications from others due to generic models. The lack of customization and precision stemming from not using proprietary data is a major drawback.

Users struggle to extract and structure data from entire websites efficiently, leading to difficulties in building custom Large Language Models (LLMs) due to the complex process of manually turning website content into usable formats for fine-tuning and vector databases. Extract and structure data from entire websites efficiently.