AI-Enhanced Video Analysis Platform for Regional Healthcare Systems
Transformed manual video analysis workflow from 8-10 hours to 2 hours per project, enabling 250% capacity increase for healthcare systems analysis.
AI-Enhanced Video Analysis Platform for Regional Healthcare Systems
Interactive demo available at the bottom of this case study
The Problem
A regional healthcare systems analysis firm faced critical capacity constraints limiting their ability to meet growing demand for healthcare workflow optimization projects:
Critical Capacity Bottleneck
Core Challenges:
- Manual video analysis consuming 8-10 hours per project using pause-screenshot-paste-annotate cycle
- Limited capacity to 20-30 annual projects when 75 projects needed for growth targets
- Senior project managers spending 150-750 hours annually on repetitive documentation tasks
- Healthcare expertise trapped in manual processes that couldn't be delegated due to specialized knowledge requirements
- Developer handoff inefficiencies requiring multiple clarification calls due to unclear field specifications
Industry: | Healthcare Systems Analysis |
Challenge: | Manual video analysis workflow bottleneck |
Growth Target: | 75 annual projects (vs. current 20-30) |
Compliance: | HIPAA-compliant environment required |
The manual process using Windows Screen Clipper → Excel → PDF was preventing the firm from scaling their healthcare systems analysis practice while maintaining the quality standards required for HIPAA-compliant environments.
The Solution
LightForge Works developed an Enhanced Multi-Modal AI Solution that preserves healthcare expertise while dramatically accelerating video analysis workflows:
🎯 Multi-Modal AI Enhancement
Key Features:
- Commentary moment detection capturing client verbal feedback during video demonstrations
- Multi-modal analysis combining audio analysis, visual attention tracking, and screen change detection
- Expert-augmented workflow preserving PM healthcare domain expertise in the loop
- AWS Serverless architecture with real-time processing and WebSocket updates
- HIPAA-compliant deployment within existing IT-managed infrastructure
- PDF output generation maintaining existing developer handoff processes
Technical Implementation:
Component | Technology | Performance |
---|---|---|
AI Analysis | AWS Bedrock Claude 3.5 Sonnet | <2 minutes for 2-hour videos |
Real-time Updates | WebSocket connections | Live progress tracking |
Screenshot Extraction | Automated contextual identification | Smart field detection |
Expert Interface | Healthcare-specific validation | Domain expertise preserved |
30/60/90 Implementation Framework
- No disruption to current operations
- Staff training included
- HIPAA compliance maintained throughout
The Impact
📈 Business Transformation Results
Immediate Results:
- 75% time reduction from 8-10 hours to ~2 hours per project analysis
- 250% capacity increase enabling 75 annual projects vs. current 20-30
- Enhanced accuracy capturing client commentary missed in manual processes
- Preserved expertise maintaining healthcare domain knowledge requirements
Business Growth:
- $25,000 investment vs. hundreds of hours of senior PM time savings annually
- Strategic resource optimization freeing senior staff for high-value activities
- Scalable growth platform supporting the firm's expansion objectives
- Improved developer handoff reducing clarification calls and project delays
💬 Client Testimonial
"The enhanced solution doesn't just speed up our process – it captures critical client feedback about field requirements that we were missing with manual analysis. This preserves the healthcare expertise that makes our work valuable while dramatically improving our capacity."
— Senior Project Manager, Regional Healthcare Systems Firm
System Interface

AI-Enhanced Video Analysis Platform showing commentary detection and field identification
This case study demonstrates how micro-applications can enhance rather than replace domain expertise, enabling healthcare organizations to scale specialized workflows while maintaining compliance and quality standards.