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Result

  • ▫️Literature review preparation time reduced by 76%
  • ▫️Citation accuracy rated at 98.3% by academic reviewers
  • ▫️87% of researchers reported discovering new research directions
  • ▫️Research productivity increased by average of 41%
  • ▫️Researchers discovered relevant papers missed by traditional searches

AI Research Paper Copilot Academic Knowledge Exploration & Synthesis Platform

Client Overview

  • ▫️Confidential (multi-disciplinary research organization)
  • ▫️Industry: Academic Research / Scientific Publishing Engagement
  • ▫️Duration: 12 weeks Team
  • ▫️Deployed: 2 AI specialists, 1 academic librarian, 1 UX researcher from TechSteck Solutions

Objectives

  • ▫️Create an AI assistant for exploring scientific literature
  • ▫️Connect related papers through semantic relationships
  • ▫️Generate comprehensive literature reviews with proper citations
  • ▫️Integrate with researchers’ existing knowledge management systems
  • ▫️Accelerate research discovery process by 3x

Solution

      • TechSteck Solutions developed a comprehensive policy RAG system using:

      • ▫️GPT-4 for scientific reasoning and synthesis
      • ▫️Semantic Scholar API for academic paper database
      • ▫️Custom academic embedding models
      • ▫️Obsidian sync for personal knowledge management
      • ▫️Citation management system with multiple format support

Workflow Architecture

  1. Research Paper Ingestion
  2.  
    • ▫️Integration with Semantic Scholar for 200M+ academic papers
    • ▫️Custom PDF parser for personal research collections
    • ▫️Citation network mapping with relationship tracking
    • ▫️Discipline-specific embedding models for improved relevance
    •  
  1.  Concept Exploration
  2.  
    • ▫️Natural language queries about research concepts
    • ▫️Temporal filtering (e.g., “papers from last 2 years on topic X”)
    • ▫️Citation-based authority ranking
    • ▫️Cross-disciplinary connection discovery
    •  
  1. Literature Review Generation
  2.  
    • ▫️Automated synthesis of key papers on specific topic
    • ▫️Proper academic citations in multiple formats (APA, MLA, Chicago)
    • ▫️Identification of research gaps and contradictions
    • ▫️Chronological development of research concepts
    •  
  1. Personal Knowledge Integration
  2.  
    • ▫️Obsidian sync for connecting personal notes with literature
    • ▫️Smart highlighting of key concepts and findings
    • ▫️Semantic linking of related concepts
    • ▫️Custom knowledge graph visualization

Conclusion

By integrating RAG capabilities with network analysis, TechSteck Solutions transformed the client’s claims processing workflow—identifying fraud more effectively, reducing investigation costs, and creating a system that continuously improves as it processes more claims data.

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