Intelligent Document Processing with AI Agent and OCR on Azure
Client Need
The client needed to enhance internal knowledge access and streamline document processing workflows. Specifically, they required an AI Agent capable of understanding natural language queries to retrieve insights from internal document repositories. Additionally, they sought a reliable tool to extract structured data from image-based files to support downstream automation.
Challenge
The company managed a large volume of internal knowledge and operational documents, many of which were stored in image formats or unstructured sources. Manually searching through these materials was time-consuming and inefficient. Furthermore, building a scalable and secure system that could process both text and image-based content—while integrating seamlessly with existing cloud infrastructure—posed a significant challenge.
Tech Stack
- Frontend: ReactJS
- Backend: Python
- Cloud Platform: Microsoft Azure (Cloud-native services)
- Deployment: Infrastructure as Code (IaC) for scalable provisioning and environment consistency
Our Solution
Tinhvan Software delivered a two-part solution:
- AI Agent for Document Querying:
We designed and developed an AI-powered assistant that enables users to query the company’s internal documentation using natural language. By leveraging Azure's cognitive services and custom NLP models, the agent understands user intent and retrieves precise, context-aware answers. - OCR and Text Extraction from Images:
A custom OCR pipeline was built to process image files, extract text content, and automatically convert it into CSV format for use in analytical and operational workflows. This enabled the client to digitize previously inaccessible data stored in image formats and unlock new value from legacy documents.
Both components were deployed within the client's Azure environment using infrastructure-as-code practices, ensuring security, scalability, and ease of maintenance.
Business Impact
- Enabled fast, natural language access to internal knowledge bases
- Significantly reduced time spent on manual document search and processing
- Converted previously unusable image data into structured, queryable formats
- Improved operational efficiency through automation of repetitive tasks
- Deployed a scalable, cloud-native system aligned with modern DevOps practices
Case studies
Intelligent Document Processing with AI Agent and OCR on Azure
Tinhvan Software built an Azure-based AI Agent and OCR tool to automate document search and image text extraction, enabling fast, secure, and structured data access. We developed an intelligent AI Agent and OCR pipeline to help enterprises query internal documents using natural language and extract structured data from image files. Built on Azure with infrastructure-as-code, the solution improves knowledge access, streamlines document processing, and enhances efficiency through secure, scalable cloud-native architecture.
Machine Learning System for Geophysical Reservoir Property Prediction (Phase 2)
Tinhvan Software built a machine learning platform to help geologists automate reservoir property analysis. The solution uses boosting models, domain-specific preprocessing, and interactive visualizations—empowering experts to interpret large-scale geophysical data faster and more accurately, with minimal technical overhead.
Petrology Prediction Model – AI for Geoscience (Phase 1)
Petrology Prediction Model, developed by Tinhvan Software for the Vietnam Petroleum Institute, applies machine learning to well log and core sample data, enabling accurate geological insights while reducing reliance on costly manual sampling and accelerating model testing in real-world exploration.