General Information:
| Industry: | Country: |
|---|---|
| Accounting services (SaaS) | USA |
| Platform: | Website: |
| Web | - |
Key Challenges:
Inefficient manual document processing leading to delays in information retrieval. Difficulty in extracting relevant data from diverse document formats. Lack of accurate and automated document categorization and tagging. Need for a streamlined solution to enhance document search capabilities.
Solution Highlights:
Comprehensive document management system leverages advanced technologies for efficient processing and understanding of diverse document types. The document processing pipeline which utilizes natural language processing (NLP) and machine learning algorithms to automate document categorization, extraction, and tagging. Enables quick and accurate extraction of key information from various document formats, including text, images, and PDFs). Automated Indexing and Categorization included AI-based algorithms which reduced the need for manual sorting and enhanced documents search capabilities by assigning relevant tags and metadata to each document. The content analysis tool which employs text analysis techniques to identify key insights and patterns within the documents for vector database. And finally a user-friendly and an intuitive web interface for users to easily upload, search, and manage documents.
Results:
Efficiency Improvement: reduction in document processing time by 50%, leading to faster information retrieval. Accuracy Enhancement: improved accuracy in data extraction and categorization, minimizing errors in document handling. Time and Cost Savings: streamlined processes result in a 30% reduction in overall customer's document management costs.
Technologies used:
- React JS
- Node JS
- LangChain
- OpenAI API
- Google Cloud Platform
- Python
- Natural Language Processing
- Machine Learning
- OCR (Optical Character Recognition)
- Pinecone
- RESTful API
- MongoDB
- Docker
- k8s
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