

Highlight 1
Excellent support for dense documents, enabling users to accurately extract data from complex tables and line items.
Highlight 2
User-friendly self-serve API that allows for quick setup and immediate use, appealing to developers.
Highlight 3
Robust error handling and validation that ensures high reliability and reduces the likelihood of incorrect data extraction.

Improvement 1
Expand file format support to include more types beyond those currently available, enhancing versatility.
Improvement 2
Focus on improving the accuracy of data extraction further to establish trust with users relying on automation.
Improvement 3
Introduce a user-friendly dashboard for monitoring extraction tasks and managing schemas.
Product Functionality
Consider adding an AI-based feature for predictive analysis to recommend schemas based on document type.
UI & UX
Enhance the user interface to make documentation more accessible and offer interactive guides for API integration.
SEO or Marketing
Develop targeted content marketing strategies that showcase case studies and integrations with popular tools to drive awareness and user acquisition.
MultiLanguage Support
Implement multi-language support in the documentation and user interface to cater to diverse global audiences.
- 1
What types of documents can be processed using tile.run?
Tile.run can process various document types, including PDFs, JPEGs, PNGs, TIFFs, and plain text.
- 2
How does the custom schema support work?
Tile.run allows users to define custom schemas, including nested objects and arrays, letting them tailor data extraction to their specific needs.
- 3
Is there a trial version or demo available?
The tile.run API offers a self-serve model that enables users to start extracting data in minutes, but specific trial offers may need to be verified on the official site.