3.3.3 PDF Pre-Processing

PDF pre-processing is a critical component of Orbit Insight's data processing pipeline, ensuring that the text extracted from PDF documents is accurate, contextually relevant, and retains the original layout as much as possible. This process is essential for maintaining the quality of downstream search and chat functionalities within the platform.

1. Text Extraction and Layout Preservation

The primary goal of PDF pre-processing within Orbit Insight is to accurately extract text from PDF documents while preserving the layout and context. This means that not only is the text content captured, but the visual structure—such as headings, tables, and columns—is also retained to ensure that the information is presented in a way that reflects its original format.

• Accurate Text Extraction: The system is designed to extract text with a high degree of accuracy, ensuring that all relevant information is captured from each PDF. This is particularly important for maintaining the integrity of the data, especially when dealing with complex documents that contain vital financial information.

• Preservation of Context: By keeping the layout intact, the pre-processing system ensures that the context in which information appears is preserved. This includes maintaining the relationships between different sections of a document, such as tables and their corresponding text, which is crucial for accurate interpretation during analysis.

[Placeholder for Before-and-After Example] Include a before-and-after example showing a PDF document pre-processing, highlighting how the text and layout are preserved.

2. Impact on Search and Chat Results

PDF pre-processing is the single most important factor affecting the quality of downstream search and chat results in Orbit Insight. The accuracy with which text is extracted and contextualized directly influences the platform's ability to deliver relevant and precise search results.

• Enhanced Search Precision: Properly processed PDFs lead to more accurate indexing, which in turn improves the precision of search queries. Users are more likely to retrieve the exact information they need when the underlying text data is well-organized and contextually accurate.

• Improved Chat Responses: The quality of text extraction also impacts the chat functionality. When PDFs are processed accurately, the AI models can better understand and respond to user queries, providing more relevant and contextually appropriate answers.

3. Challenges in PDF Processing

Processing PDFs presents several challenges, especially given the variety of document types and formats that Orbit Insight must handle. The system is designed to address these challenges with a combination of advanced technologies and customized processing pipelines.

• OCR for Scanned Documents: For PDFs that are scan copies rather than digitally generated files, Optical Character Recognition (OCR) is required to convert images of text into machine-readable text. This process is crucial for making sure that all text is captured, even from non-digital sources.

• Layout Detection: Some PDFs have complex layouts with intricate designs, such as multi-column formats, tables, or embedded images. Accurately detecting and breaking down these layouts is essential for maintaining the integrity of the document during text extraction. This ensures that the extracted text remains logically organized and useful for downstream processes.

4. Cost Considerations and Optimization

While processing a few hundred or thousand PDFs may be relatively inexpensive, scaling up to millions of documents per year presents significant cost challenges. Orbit Insight has developed an internal PDF parsing pipeline that balances the need for high-quality text extraction with cost efficiency.

• Cost vs. Quality Balance: Using the most powerful PDF parsing models for every document would guarantee the highest quality but at a prohibitive cost when dealing with large volumes. To address this, Orbit Insight employs a tiered approach, utilizing state-of-the-art models where necessary while relying on more cost-effective methods for simpler documents.

• Internal PDF Parsing Pipeline: Orbit Insight’s internally developed PDF parsing pipeline is designed to benchmark against the best available models, ensuring that the quality of text extraction remains high without incurring excessive costs. This approach allows the platform to scale efficiently, processing large volumes of documents while maintaining a balance between quality and cost.