Phlow AI
Clinical Research

Medical Literature Intelligence

AI-powered research assistant that synthesizes findings from thousands of medical publications.

50x
Faster literature review
10K+
Papers Analyzed
3min
Avg Synthesis Time
98%
Relevance Accuracy
01

The Challenge

Research teams were spending weeks manually reviewing hundreds of papers for each systematic review. The volume of published medical literature made comprehensive reviews nearly impossible.

Critical findings were being missed simply because no human could read fast enough. Teams were forced to narrow their scope, potentially missing relevant evidence.

The manual process introduced inconsistency in how papers were evaluated and summarized, affecting the quality of research conclusions.

We knew important research was out there, but we simply could not read fast enough to find it all.

2-3wks
Average review time
500+
Papers per review
02

The Solution

We developed an intelligent literature analysis system that processes thousands of papers, extracts key findings, and synthesizes insights relevant to specific research questions.

The system identifies patterns across studies, highlights contradictions, and surfaces the most relevant evidence based on methodology quality and relevance scores.

Researchers can now ask natural language questions and receive comprehensive answers backed by cited sources.

Key Features

  • Automated paper ingestion from PubMed and journals
  • Key finding extraction with methodology assessment
  • Cross-study pattern and contradiction detection
  • Natural language query interface
  • Automatic citation and source tracking
03

Implementation

Technical Approach

  • Claude API for deep semantic analysis
  • PubMed API integration for paper retrieval
  • Vector database for semantic search
  • FastAPI backend with async processing
  • React dashboard for exploration

Change Management

  • Research team workshops on effective prompting
  • Validation studies comparing AI vs manual review
  • Iterative refinement based on researcher feedback
  • Integration into existing research workflows
04

Results & Impact

50x
Faster Review
10K+
Papers Analyzed
3min
Avg Synthesis Time
98%
Relevance Accuracy
  • Systematic reviews completed in days instead of weeks
  • Research scope expanded without additional headcount
  • Higher confidence in comprehensive evidence coverage
  • Researchers focus on analysis rather than data gathering

Technology Stack

Claude APIPythonPostgreSQLFastAPIReact