Why Choose Our Knowledge Mining Service
Revolutionize Your Data Analysis with Knowledge Mining
Unstructured data holds valuable insights, but extracting them can be complex. Our Knowledge Mining Service leverages Azure Blob Storage, Cognitive Search, and GPT-powered RAG to transform your raw data into a searchable, interactive knowledge base. With a conversational AI interface, uncover insights faster and make informed decisions.
Revolutionize Your Data Analysis with Knowledge Mining
Unstructured data holds valuable insights, but extracting them can be complex. Our Knowledge Mining Service leverages Azure Blob Storage, Cognitive Search, and GPT-powered RAG to transform your raw data into a searchable, interactive knowledge base. With a conversational AI interface, uncover insights faster and make informed decisions.
How It Works
Ingestion
All unstructured data (e.g., Service Desk ticket descriptions) is ingested and securely stored in Azure Blob Storage, enabling scalable and cost-effective data management.
Enriching
Documents are processed using Azure Cognitive Search, which builds an enriched index for efficient retrieval. The indexing process includes pre-trained AI models for:
- Key phrase extraction to identify important information.
- Named entity recognition for pinpointing specific details like products, issues, and clients.
- Semantic similarity analysis to relate different tickets or feedback with similar contexts.
RAG Integration:
- Retrieval: Relevant content is retrieved and contextualized using OpenAI’s GPT models.
- Generation: The GPT models summarize, contextualize, and present the retrieved content, providing coherent and comprehensive responses.
- This architecture ensures that responses are based on the most relevant and up-to-date indexed data, improving accuracy and relevance.
Interactive Chat Interface
A conversational interface, built using Azure Bot Framework, serves as the front-end for users to interact with the knowledge base.
The chat system supports:
- Multilingual queries and responses, allowing users to communicate in their preferred language.
- Context-aware conversation flow, ensuring continuity across multiple interactions.
The interface is accessible via web applications, Microsoft Teams, or custom integrations.
How It Works
Ingestion
All unstructured data (e.g., Service Desk ticket descriptions) is ingested and securely stored in Azure Blob Storage, enabling scalable and cost-effective data management.
Enriching
Documents are processed using Azure Cognitive Search, which builds an enriched index for efficient retrieval. The indexing process includes pre-trained AI models for:
- Key phrase extraction to identify important information.
- Named entity recognition for pinpointing specific details like products, issues, and clients.
- Semantic similarity analysis to relate different tickets or feedback with similar contexts.
RAG Integration:
- Retrieval: Relevant content is retrieved and contextualized using OpenAI’s GPT models.
- Generation: The GPT models summarize, contextualize, and present the retrieved content, providing coherent and comprehensive responses.
- This architecture ensures that responses are based on the most relevant and up-to-date indexed data, improving accuracy and relevance.
Interactive Chat Interface
A conversational interface, built using Azure Bot Framework, serves as the front-end for users to interact with the knowledge base.
The chat system supports:
- Multilingual queries and responses, allowing users to communicate in their preferred language.
- Context-aware conversation flow, ensuring continuity across multiple interactions.
The interface is accessible via web applications, Microsoft Teams, or custom integrations.
Applications Across Industries
Discover the Power of Knowledge Mining
Request a Demo. Book a session with our expecialists to discuss your specific needs of your knowledge base.