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AI-Driven SaaS Platform Enhancement for CNC Manufacturing Quotation Automation
  1. case
  2. AI-Driven SaaS Platform Enhancement for CNC Manufacturing Quotation Automation

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AI-Driven SaaS Platform Enhancement for CNC Manufacturing Quotation Automation

leobit.com
Manufacturing
Information Technology
Artificial Intelligence

Business Challenge Overview

The client required scaling their existing CNC quotation platform with advanced AI capabilities but lacked in-house expertise for developing machine learning integrations, cloud optimization, and real-time 3D modeling features. They needed a partner to handle complex technical challenges while maintaining GDPR compliance and system performance.

About the Client

Swiss high-tech company specializing in AI/ML solutions for manufacturing automation, with expertise in mechanical engineering and contract manufacturing.

Project Objectives

  • Develop AI-driven modules for automated CNC production time estimation
  • Integrate machine learning pipelines for continuous model improvement
  • Implement GDPR-compliant data security and encryption protocols
  • Optimize cloud infrastructure to reduce operational costs
  • Enable real-time 3D model visualization and collaboration features

Functional Requirements Summary

  • AI assistant for machine setup/running time estimation
  • 3D model processing with Three.js integration
  • Centralized secure database for technical drawings and quotes
  • SendGrid API for client communication workflows
  • Geolocation-based manufacturer directory

Preferred Technology Stack

.NET Framework/.NET 5
Azure WebJobs/Quartz.NET
ActiveMQ/MongoDB
Docker containerization
HTML5/Sass frontend

Critical System Integrations

  • SendGrid API for email automation
  • Azure Geolocation service
  • Three.js 3D rendering library
  • ML model training pipelines

Non-Functional Requirements

  • GDPR-compliant data encryption at rest/transit
  • Horizontal scalability for 10x user growth
  • Sub-second API response times for ML calculations
  • 99.95% system uptime SLA
  • Multi-tenancy architecture for SaaS delivery

Expected Business Impact

Enable CNC manufacturers to reduce quotation preparation time by 70%, achieve 30% lower cloud infrastructure costs through optimization, and improve quote accuracy through self-learning AI models. The platform will facilitate faster client onboarding through automated 3D model analysis and real-time collaboration tools.

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