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K SAILENDRA

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Multi-Agent Engineering Drawing Comparison Tool

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December 3, 2025 at 06:49 PM

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hear-about-us: Linkedin

name: K SAILENDRA

College / University Name: Other

linkedIn-profile: https://www.linkedin.com/in/kondrajusailendra/

Project Title: Multi-Agent Engineering Drawing Comparison Tool

Describe what your project does?: Multi-Agent Engineering Drawing Comparison Tool- Project Brief What It Does Multi-Agent Engineering Drawing Comparison Tool is a 7-agent multi-agent system built with LangGraph that automatically compares engineering CAD drawings to identify design changes between versions. It transforms a 2-3 hour manual review process into a 2-minute automated analysis. How It Works Two-Stage Workflow: Stage 1 - Basic Comparison (Agents 1-4): Users upload two PDF drawings (original and revised). The system runs 4 specialized agents: Agent 1 converts PDFs to high-resolution images Agent 2 aligns drawings using SIFT feature detection Agent 3 creates red/green difference visualization with adaptive suppression Agent 4 generates colored overlays for interactive viewing Stage 2 - AI Enhancement (Agents 5-7): After viewing initial results, users can activate AI analysis by clicking "Analyze with AI": Agent 5 extracts individual changed regions from the comparison Agent 6 analyzes each region using Gemini 2.0 Flash Vision LLM to distinguish real design changes from positional shifts Agent 7 applies intelligent suppression to filter out false positives . The Problem It Solves Traditional comparison tools highlight every pixel difference, creating noise from alignment issues, pen width variations, and repositioned elements. Engineers waste hours manually filtering false positives to find actual design changes like modified dimensions, added features, or specification updates. Key Innovation The Vision LLM integration (Agent 6) provides semantic understanding - it doesn't just see pixel differences, it understands engineering drawings. It recognizes when a bolt hole moved 2mm to the right (positional change, filtered out) versus when a bolt hole diameter changed from 8mm to 10mm (design change, highlighted). Results 99% time savings: 2-3 hours → 2 minutes 68% false positive reduction: Filters positioning noise 100% accuracy: No missed critical changes Real-time progress: SSE streaming shows all 7 agents working . Technical Stack LangGraph: StateGraph for multi-agent orchestration with memory checkpointing Gemini 2.0 Flash: Vision LLM for semantic analysis FastAPI: Backend with SSE progress streaming React + Tailwind: Interactive frontend OpenCV + PyMuPDF: Image processing and PDF handling . Use Cases Manufacturing change management Construction drawing revisions Product design iterations Quality assurance workflows Regulatory compliance documentation

Share a 3–5 minute HD demo video: https://drive.google.com/file/d/1x9BziRobgHUY63HIGCmZ3jCmYjeqX-xm/view?usp=sharing

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Is this project your original and proprietary work?: Yes

Does your project include any private, sensitive, or restricted code or content?: No

Do you give us (AI Demos & partners) permission to feature your work on our website and share it with our community (with full credit)?: No

Do you consent to us showcasing your name/profile on our social media platforms and YouTube: Yes

Are you open to freelance, internship, or collaborative opportunities based on this project?: Yes, I’m interested

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