Transforming business processes with Generative AI

SITUATION:

In the fast-paced business world, staying ahead demands relentless innovation and efficiency. For one of our clients, embracing Generative AI has proven to be a transformative step forward.

• The client relies on an Enterprise Content Management (ECM) platform for document storage, but they struggled to extract actionable insights from their large collection of unstructured data.
• With multiple brands under their umbrella, each using different invoice formats, tracking orders became complicated, leading to inefficiencies and unintended customer freebies.
• The challenge was further intensified by the increasing volume of multilingual documents, making it difficult to maintain operational efficiency and ensure easy access to important data across the organization.

Our innovative AI solutions have revolutionized their document management processes, enabling them to overcome these critical challenges and set a new standard for efficiency in their industry.

SOLUTION:

To address these challenges, we implemented four cutting-edge Generative AI solutions: Invoice Scanner, Document Summarizer, Document Translator, and Document Chat. These solutions transformed the client’s document management process, leading to remarkable improvements in productivity and accuracy.

These implementations showcase the innovative potential of Generative AI, transforming the interaction between businesses and unstructured data. The nuanced understanding and response generation capabilities of Generative AI mimic human cognitive abilities, making these solutions truly revolutionary.

1. Invoice Scanner: Utilizes advanced OCR and AI models to accurately recognize and categorize invoice data.
2. Document Summarizer: Leverages state-of-the-art language models to understand context and generate relevant summaries.
3. Document Translator: Integrates multilingual models from OpenAI, ensuring seamless translations that respect linguistic nuances.
4. Document Chat: Employs conversational AI for intuitive and efficient document interaction through natural language processing.

Tech Stack: Python, FastAPI, Celery, Azure OpenAI API, React, Docker, Azure

Implementation details

Invoice Scanner

• Document Processing: Digitized invoices are processed through a custom Intelligent Document Processor, designed for various document formats.
• Data Extraction: Using advanced OCR technologies and Large Language Models (LLMs), key information is extracted with high precision.
• Validation: A Human-In-The-Loop (HITL) system ensures the accuracy of AI-generated outputs through manual verification and correction.

Document Summarizer

• Document Parsing: Documents are processed using the Intelligent Document Processor.
• Summary Generation: LLMs generate precise summaries based on custom parameters.
• Output Storage: Summaries are stored in a ‘Too Long; Didn’t Read’ (TLDR) format for easy retrieval and review.

Document Translator

• Language Processing: Documents are processed using the Intelligent Document Processor.
• Translation Mechanics: LLMs tailored for specific languages handle translations, incorporating custom parameters for linguistic nuances.
• Custom Vocabulary Support: Supports custom vocabularies and industry-specific jargon for accurate and contextually appropriate translations.

Document Chat

• Document Chunking: Documents are segmented to manage LLM token limitations.
• Vectorization: Each segment is converted into vector embeddings and stored in a vector database.
• Semantic Search: User queries are converted into vector embeddings, and a semantic search retrieves top relevant results.
• Response Generation: Extracted information is parsed through an LLM to generate coherent, contextually aware, and human-like responses.
• This robust implementation framework ensures each POC not only meets but exceeds operational requirements, setting a new standard in document processing technologies.

OUTCOME:

The deployment of these implementations has delivered transformative outcomes for our client:

• Invoice Scanner: Digitization and tracking of invoice data.
• Document Summarizer: Enhanced productivity by providing quick insights.
• Document Translator: Increased global reach and communication efficiency.
• Document Chat: Improved user experience and document handling efficiency, addressing attrition problems by serving as a co-pilot for support engagements.

This solution alone reduced document handling time by 40% and decreased manual errors by 20%. Additionally, customer complaint rates dropped by 20% due to improved invoice tracking on a digital platform, setting a new benchmark for operational efficiency in the industry.

Future outlook

The possibilities for Generative AI in document processing are vast. Future enhancements could include:

• Multi-Modal Support: Integrating text, tables, and images for enhanced context awareness and comprehensive understanding.
• Hybrid RAG Approach for Document Chat: Implementing a hybrid Retrieval-Augmented Generation (RAG) strategy to improve the accuracy and relevance of data retrieval using knowledge graphs and other databases.
• Dynamic Prompt Databases: Developing databases of prompts that dynamically fine-tune based on input data, ensuring more tailored and effective AI interactions.

The goal is to further reduce document handling time, increase employee productivity, improve tracking and resolution of customer complaints, and minimize the distribution of freebies to dissatisfied customers. This will help decrease customer churn and reduce unnecessary costs to the company.