Convert Receipt to Arrow

Receipts show important info about what you buy and how you pay. Our system can pull structured data from many types of receipts. We can handle PDFs, images like PNG or JPEG, and scanned documents. We capture all the key details you usually find on store or service receipts.

We can pull out these main parts:

• Store name and address
• When you bought it
• List of what you bought (including name, how many, unit, and price)
• Subtotal, tax, and total amounts
• How you paid

This is really helpful for:

• Tracking and managing expenses
• Automating bookkeeping and financial records
• Automating data entry from paper or digital receipts
• Financial analysis and reporting

By pulling data from different receipt formats, you can easily digitize and organize your financial records. This saves time and cuts down on data entry mistakes. You can then use this data in accounting software, expense reports, or other financial management systems.

Apache Arrow is a cross-language platform for in-memory data. It defines a standard columnar memory format for flat and hierarchical data that works across different programming languages. This format is optimized for efficient analytics on modern hardware like CPUs and GPUs.

Arrow can handle complex nested data structures and lets you query and work with specific columns without reading the entire dataset.

Key Features

• Columnar memory format for flat and hierarchical data
• Works with any programming language
• Optimized for analytics and modern hardware
• Supports complex nested data structures
• Enables efficient zero-copy reads

Use Cases

Apache Arrow shines in scenarios like:

• Big data processing and analytics
• Machine learning and AI pipelines
• Data exchange between different systems and languages
• High-performance computing applications

Its efficient memory layout and standardized format make it a great choice for applications that need fast data processing and compatibility between different tools and languages.