PH Deck

Manual data entry of bills or invoices into systems is a time-consuming process with a high risk of errors and no dependency on template.

Users need efficient methods to extract data from websites, but they face challenges with traditional methods.

Businesses and individuals often struggle with manual data entry from invoices and receipts, which is time-consuming, prone to errors, and inefficient for processing and storage.

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 experience data loss or corruption on their Windows devices like hard drives, SSDs, USB drives, and memory cards. The old solution is relying on standard data maintenance and backup practices, which can often fail. The drawbacks are that traditional retrieval methods are not sufficient when devices experience severe data corruption or mechanical failure, leaving users unable to recover critical data efficiently.

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.

Users often need to permanently delete sensitive files, folders, and drives to protect privacy and confidential information. Traditional methods of deletion may leave data recoverable, compromising security. The drawback of the old situation is that even after deleting data, it can often be recovered using simple software tools, thus failing to protect sensitive information effectively. Data recoverability after deletion.

Users currently rely on traditional methods of gathering financial data, such as manual searches on financial websites or outdated data platforms. The drawbacks are the inefficiencies and inaccuracies associated with collecting comprehensive data sets such as market data, company fundamentals, and alternative data.

Users face difficulties in accessing structured data from LinkedIn profiles, companies, and jobs due to restrictions and limitations imposed on data access.