ForgeIQ — Multimodal AI Engineering Design Intelligence

ForgeIQ is a multimodal AI engineering intelligence platform that converts engineering artifacts (photographs of mechanical components, CAD screenshots, engineering sketches, technical drawings, datasheets, or damaged parts) into structured, professional engineering reviews.

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Problem Addressed

Engineers, product designers, robotics teams, and manufacturing consultants often need rapid initial reviews of mechanical components for DFM (Design for Manufacturability), materials suitability, risk & failure analysis, and quality inspection. Manual early-stage engineering audits can take days. ForgeIQ leverages Gemini multimodal intelligence to analyze visual and textual artifact evidence alongside operating context, providing structured, actionable engineering reports in seconds.

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Main Features

1. Multimodal Artifact Analysis: Accepts component photos, CAD screenshots, engineering sketches, technical drawings, and technical PDFs.
2. 7 Tailored Analysis Modes:
   • General Engineering Review
   • Design for Manufacturability (DFM)
   • Materials and Process Selection
   • Failure and Risk Analysis (FMEA)
   • Quality Inspection Checklist
   • Robotics and Mechanism Review
   • Medical Device and Product Review
3. Structured Engineering Report:
   • Executive Summary
   • Artifact Identification & Confidence Level
   • Functional Purpose & Interacting Interfaces
   • Geometry & Stress Concentration Observations
   • Material Assessment & Candidate Alloy/Polymer Tradeoffs
   • Manufacturing & DFM Optimization
   • Failure Risk Analysis & Qualitative FMEA Table
   • Quality Inspection Checklist with Interactive Checkboxes
   • Prioritized Engineering Recommendations (Critical/High/Medium/Low)
   • Missing Data Checklist
4. Contextual Q&A Follow-up Assistant: Conversational engineering assistant grounded in the uploaded artifact and generated report context. Distinguishes hard facts, assumptions, and recommendations.
5. Report Export: Copy formatted report text or download as clean Markdown file.
6. Built-in Demo Samples: Pre-packaged engineering artifacts (UAV Motor Mount Node, Orthopedic Bone Plate, Robotic Actuator Housing) for immediate live or preset evaluation.

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Technology Stack

• Frontend: React 18 / 19, TypeScript, Tailwind CSS v4, Lucide React icons
• Backend Runtime: Node.js, Express, ESBuild, TSX
• AI Engine: @google/genai TypeScript SDK (Server-side Gemini 3.6 Flash model with structured JSON Schema)

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Local Setup & Configuration

1. Prerequisites

• Node.js 20+
• npm

2. Environment Variables

Create a .env file in the project root:

# Required for Gemini API calls
GEMINI_API_KEY="your_gemini_api_key_here"

# App URL
APP_URL="http://localhost:3000"

In Google AI Studio, GEMINI_API_KEY is automatically injected into the server runtime via the Settings > Secrets panel.

3. Installation & Running

# Install dependencies
npm install

# Start development server
npm run dev

The application will be accessible at http://localhost:3000.

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Safety & Engineering Limitations

• Preliminary Analysis Only: ForgeIQ output represents preliminary AI-assisted observations and must be validated by a licensed professional engineer using full engineering drawings, physical testing, simulations (FEA/CFD), and domain standards.
• No Fabricated Data: ForgeIQ explicitly refuses to fabricate dimensions, exact numerical tolerances, or regulatory approvals when evidence is insufficient.
• Medical Devices: Output is framed strictly as early-stage engineering guidance and does not claim FDA/CE regulatory approval or diagnostic validity.

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Future Improvements

• STEP / IGES CAD file 3D mesh rendering and stress heatmap visualization.
• Direct export to PDF and formal PDF/A technical submission packages.
• Integration with material databases (e.g., MatWeb, Ansys Granta).
• Automated FEA meshing script generation for Abaqus or ANSYS.

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Exporting & Pushing to GitHub

To export or push this project to GitHub:

1. Initialize git: git init
2. Add remote repository: git remote add origin <your-github-repo-url>
3. Commit and push:

   git add .
   git commit -m "Initial commit of ForgeIQ application"
   git branch -M main
   git push -u origin main