Large Language Models (LLMs) are effective tools, but processing lengthy documents such as reports, legal files, or research papers presents challenges due to token limits and high costs, making direct processing inefficient. To address this, a structured approach is necessary, involving breaking the document into smaller, manageable sections, using chunking with overlaps to maintain context, and dividing the workflow into stages like extraction, summarization, and synthesis. Selecting the right model for each task, such as specialized APIs for OCR or text extraction and smaller models for classification, enhances accuracy and cost-effectiveness. Eden AI assists in orchestrating this process by providing access to multiple AI models through a single platform, allowing for efficient management, cost monitoring, and optimized document analysis workflows without the need for complex orchestration coding.