Advanced GenAI-based Aluminum System Design & Engineering Digital Assistant for ALUMIL
- The client
ALUMIL
ALUMIL - A leading global manufacturer of architectural aluminum systems, ALUMIL is known for its innovative and sustainable solutions. The company is one of the largest and most advanced industries in Europe for the design and production of high-quality aluminum products for building applications.
ALUMIL - A leading global manufacturer of architectural aluminum systems, ALUMIL is known for its innovative and sustainable solutions. The company is one of the largest and most advanced industries in Europe for the design and production of high-quality aluminum products for building applications.
- The case
UBITECH AiLabs was contracted by ALUMIL to design, implement, and deploy an AI-powered digital assistant tailored for engineers, architects, and fabricators working with aluminum system designs. This advanced digital assistant leverages UBITECH's PYTHEA platform, which is based on Large Language Models (LLMs) and integrates cutting-edge Generative AI (GenAI) technologies. The primary goal of this initiative was to streamline the complex processes involved in aluminum system design, enhance the efficiency of design workflows, and reduce the likelihood of errors in component specification.
The GenAI-based digital assistant processes user inputs—such as dimensions, sound insulation requirements, and wind pressure specifications—and provides optimized recommendations. The assistant also generates detailed outputs like part numbers and material cuts (Bill of Materials) by leveraging a robust knowledge graph-based Retrieval-Augmented Generation (RAG) strategy that accesses ALUMIL’s comprehensive product data.
The Objectives:
The GenAI-based digital assistant processes user inputs—such as dimensions, sound insulation requirements, and wind pressure specifications—and provides optimized recommendations. The assistant also generates detailed outputs like part numbers and material cuts (Bill of Materials) by leveraging a robust knowledge graph-based Retrieval-Augmented Generation (RAG) strategy that accesses ALUMIL’s comprehensive product data.
The Objectives:
- Increase Efficiency:
By providing fast, accurate design suggestions tailored to specific user requirements, the AI assistant enables engineers to save valuable time. - Reduce Errors:
The system minimizes the risk of incorrect component selections, thereby enhancing the reliability of the design process. - Enhance User Experience:
The solution delivers personalized and precise responses, aligning closely with user needs and improving overall satisfaction.
- The challenges
- Complex Knowledge Integration:
The need to efficiently process and integrate extensive product data stored in a vector graph database required a sophisticated AI solution with dynamic knowledge retrieval capabilities. - Specialized User Requirements:
The diverse needs of users—including engineers, architects, and fabricators—meant that the digital assistant had to cater to varying expertise levels and provide tailored, actionable insights. - Accuracy and Optimization:
Ensuring the AI assistant provided optimal recommendations for complex design specifications was critical, necessitating the use of advanced machine learning algorithms and a Retrieval-Augmented Generation (RAG) strategy. - User Trust and Adoption:
Introducing a new AI-based tool in a traditionally manual industry required a focus on user trust and seamless integration into existing workflows to promote adoption.
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