Leo
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About
Leo is an AI-powered engineering design co-pilot developed specifically for mechanical engineers and leading engineering firms. Unlike general-purpose AI tools, Leo is built upon a proprietary Large Mechanical Model (LMM) that understands the unique constraints of physical products. The platform serves as a central hub for engineering intelligence, enabling teams to query their internal Product Lifecycle Management (PLM) data alongside over one million trusted engineering sources. By grounding its answers in verified data rather than general internet information, it provides engineering-grade accuracy for technical decision-making and knowledge retrieval. The tool's functionality extends across the entire design lifecycle, from initial concepting to detailed technical analysis. Engineers can use the natural language interface to perform complex engineering calculations, such as stress analysis or material selection, without relying on manual spreadsheets. Leo identifies the necessary formulas, executes the calculations, and cites its sources for verification. Additionally, the platform features a massive part retrieval system, allowing users to find optimal components from internal PLM databases or a catalog of over 120 million vendor parts. This helps increase part reuse and ensures design quality by selecting the most appropriate components for specific requirements. Leo is primarily designed for mechanical engineers, systems engineers, and product design teams working on complex hardware, robotics, or medical devices. It integrates directly into popular CAD editors, allowing for a workflow where the AI acts as a natural extension of the engineer’s mind. The system is multi-modal, meaning it can process textual requirements, hand-drawn sketches, 2D images, and 3D CAD files. This flexibility allows engineers to move from rough ideas to DFMA-compliant products faster than traditional manual processes. What distinguishes Leo from general models is its domain-specific training. While standard models treat words as tokens, Leo’s LMM was trained using machine parts as tokens, learning how components like bearings and bolts interact within functional assemblies. This allows the AI to recognize physical constraints and engineering logic that general models miss. Furthermore, the platform prioritizes enterprise-grade security, offering SOC 2 certification and GDPR compliance with a guarantee that user data is not used for model training, making it suitable for high-stakes industrial environments.
Pros & Cons
Built on a patented Large Mechanical Model specifically for mechanical engineering constraints.
Provides access to over 120 million vendor parts for improved sourcing and part reuse.
Grounded in verified engineering sources and internal PLM data to prevent hallucinations.
Supports multi-modal inputs including hand-drawn sketches and 3D CAD files.
Offers SOC 2 certification and GDPR compliance with a policy against training on user data.
Primarily focused on mechanical engineering, which may limit utility for other engineering disciplines.
Integration capabilities are currently optimized for specific CAD platforms like Onshape.
Requires connection to internal PLM systems to unlock its full organizational knowledge potential.
Use Cases
Mechanical engineers can automate complex stress analysis and material selection calculations directly within their design workflow.
Design teams can search through legacy PLM data and 120 million vendor parts to increase component reuse across projects.
Product designers can convert hand-drawn sketches and textual requirements into DFMA-compliant concepts using the multi-modal AI.
Engineering leads can ensure team-wide adherence to best practices by grounding AI responses in verified organizational knowledge.
Platform
Task
Features
• multi-modal input support
• enterprise security (soc 2)
• dfma-compliant design
• cad software integration
• automated engineering calculations
• 120m+ vendor part search
• plm knowledge retrieval
• large mechanical model (lmm)
FAQs
What sources does Leo use for its answers?
Answers are grounded in internal PLM data and over one million verified engineering sources. This ensures that technical responses are accurate and specific to the engineering domain rather than generic internet data.
Can Leo perform technical calculations?
Yes, Leo can identify formulas and run calculations for tasks like stress analysis and material selection. It cites its sources and provides the working logic, eliminating the need for manual spreadsheets.
Does Leo integrate with CAD software?
Leo is built to integrate directly with professional CAD environments such as Onshape by PTC. This allows engineers to access AI assistance for part retrieval and design validation without leaving their primary workspace.
What is a Large Mechanical Model (LMM)?
The Large Mechanical Model is a proprietary foundational model trained on millions of physical products. It treats machine parts as tokens to understand physical constraints and manufacturing logic that general LLMs might miss.
How is user data handled and protected?
The platform is SOC 2 certified and GDPR compliant, ensuring that sensitive engineering data is protected with industry-standard protocols. Additionally, the company maintains a strict policy of zero training on customer data.
Pricing Plans
Enterprise
Unknown Price• PLM Integration
• Large Mechanical Model Access
• 120M+ Vendor Part Database
• Automated Engineering Calculations
• CAD Editor Integration
• SOC 2 Security Compliance
• GDPR Compliance
• White-glove Support
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
Average Rating: 5.0
Average Rating: 5.0
5 Stars:
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User Reviews
8/22/2024
OMG, the way you do mechanical design will NEVER be the same.. The AI revolution has finally arrived in product design! I know it be cause we built it.. ;)
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