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LTM Data & AI ContentSearch
https://catalogartifact.azureedge.net/publicartifacts/ltim.ltimindtree_dataandai_contentsearch-d0b6ffc1-4bba-48c0-8197-1b90ca8f02f8/image3_LTM216X216px.png

LTM Data & AI ContentSearch

LTIMindtree Limited

Preise Free

Bring Business Creativity to Unlock Enterprise Content Faster With Retrieval-Augmented Search, Stronger Language Consistency, and More Usable Answers Across Large Document Estates.

ContentSearch is a retrieval-augmented generation (RAG) application that helps organizations search large document sets, generate more contextual responses, and maintain language consistency across outputs.

Built on Azure OpenAI and Azure AI Search, it gives users a conversational way to interact with enterprise content and find relevant information faster.

The solution supports large-scale document retrieval, enrichment, and response generation across multiple formats and data sources.

It is designed to reduce the effort required to search, interpret, and reuse enterprise knowledge while improving answer quality and usability.

Key Features

  • NLP-Enhanced Interaction: Uses semantic search and summarization to help users retrieve relevant information from documents faster and with less manual effort
  • Prompt Engineering for Precision: Applies prompt design techniques to improve response quality and reduce ambiguity in task execution.
  • Robust Search Capabilities: Uses Azure AI Search to support keyword, vector, hybrid, and semantic search across large data volumes.
  • Data Enrichment Functions: Supports OCR, translation, keyword extraction, key phrase extraction, and image captioning to make unstructured content more usable.
  • Versatile Data Format Handling: Works across formats such as PDF, HTML, and DOC to support broader document compatibility.
  • Diverse Data Source Integration: Connects with Blob Storage and can extend to Azure Cosmos DB, Azure Tables, and SharePoint folders.
  • Auto-Incremental Indexing: Keeps content indexes current as new data is added.
  • Advanced Chunking Strategies: Uses hierarchical auto-merge and sentence-window chunking.
  • Content Safety Measures: Applies controls for safer interactions and compliant data handling.

    • Deliverables

  • Applicable Azure Solution Set: Defined view of Azure technologies used.
  • Retrieval Performance Analysis: Assessment of chunking strategies.
  • Solution Performance Analysis: Performance review using multiple metrics.
  • Skill Gap Assessment: Evaluation of staff readiness.
  • Adoption Recommendations: Guidance for implementation.
  • License Review: Review of licensing needs.

    • Business Model

  • Azure-Based Service Offering: Delivered via Microsoft Marketplace.
  • Consulting Services Support: Includes implementation, training, and support.
  • Business Value: Improves data utilization and decision-making.
  • Partnership Potential: Enables collaboration with Azure partners.

    • Auf einen Blick

    https://catalogartifact.azureedge.net/publicartifacts/ltim.ltimindtree_dataandai_contentsearch-d0b6ffc1-4bba-48c0-8197-1b90ca8f02f8/image1_Contentsearch.png