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.

Users currently extract data manually or with basic scripts from documents, websites, and files, leading to time-consuming processes and high error rates.

Users need to extract structured data from various sources but rely on traditional web scraping limited to websites, which cannot capture data from desktop apps, mobile apps, or games and may lack accuracy.

Users need to manually extract structured data from unstructured sources like web pages, forms, and screenshots, which is time-consuming, error-prone, and requires technical expertise

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 manually extract data from invoices and receipts, leading to time-consuming processes and high error rates.

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 need sports data and odds for applications but rely on fragmented or unreliable sources. Fragmented or unreliable sources cause delays and inaccuracies in sports data integration.