Qualitative Insights Extraction Engine: Turns Unstructured Data into a Searchable Knowledge Base
The Challenge
ProcDNA's Solution
Qualitative Insights Extraction Engine
ProcDNA developed a scalable, GenAI-powered solution that converts unstructured documents into a structured, queryable knowledge base, enabling business users to access insights via natural language.
Automated Document Ingestion
Ingests raw PDF and DOCX files and applies a strict JSON schema to guide LLM-based extraction of domain-specific attributes.
LLM-Powered Extraction Engine
Acts as a domain-specific NLP agent to extract key entities with enforced formatting and high schema compliance.
Data Flattening & Deduplication
Transforms complex hierarchical outputs into flat, analysis-ready datasets and consolidates them into a centralized Single Source of Truth.
Configurable Team Chatbots
Enables tailored chatbots for functions such as Medical Affairs and Market Access.
Context-Based Text-to-SQL
Automatically converts business questions into executable SQL queries for self-serve analytics.
Dual-View Insights Delivery
Provides both interactive data tables and natural language summaries for faster decision-making.
Smart Intent Recognition
Differentiates conversational and analytical queries to optimize performance and response accuracy.
Multi-Session Context & Memory
Supports concurrent users and conversational history for seamless follow-up queries.
Impact
Accelerated Time-to-Insight
Reduced insight discovery from days of manual review to near real-time automated extraction.
100% Schema Compliance
Ensured standardized, error-free structured outputs across documents, creating a trusted data foundation.
Instant Query Resolution
Cut turnaround time for complex business queries from days (via IT tickets) to seconds through self-serve natural language queries.
Scalable Data Readiness
Proven capability to ingest, flatten, and deduplicate high volumes of diverse file formats, enabling enterprise-scale deployment.
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