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{{Infobox company
| name = Leo AI, Inc.
| type = [[Privately held company|Private]]
| industry = [[Software]], [[Artificial intelligence]], [[Computer-aided design|CAD]]
| founded = 2023; 2 years ago
| founders = [[Dr. Maor Farid]] (CEO)<br>[[Mordechai Moravia]] (CTO)
| headquarters = [[Cambridge, Massachusetts]], U.S.
| area_served = Worldwide [cite: 6]
| key_people = Fielder Hiss (Advisor)<br>Saar Yoskovitz (Advisor)<br>Bertrand Sicot (Advisor)
| products = Leo<br>Large Mechanical Model (LMM)
| services = Engineering design automation, [[Product lifecycle management|PLM]] integration
| number_of_employees = ~25
| website = {{URL|https://www.getleo.ai/}}
}}

'''Leo AI''' acts as an artificial intelligence-driven design assistant specifically tailored for mechanical engineering professionals. The system is educated on extensive engineering standards and datasets, enabling it to resolve technical inquiries, address design challenges, locate standard components, and produce 3D product concepts and CAD parts.<ref name=":7"/><ref name=":4"/><ref name=":5"/><ref name=":35"/>

==Software==
Leo AI, Inc. is a technology firm based in the United States specializing in engineering-grade AI software. The enterprise was established in 2023 in [[Cambridge, Massachusetts]],<ref name=":3"/> by mechanical engineers Dr. Maor Farid (Chief Executive Officer) and Mordechai Moravia (Chief Technology Officer).<ref name=":2"/>

The company developed Leo, recognized as the inaugural AI system designed by mechanical engineers for their peers. The platform utilizes a domain-specific foundational technology known as the Large Mechanical Model (LMM), capable of interpreting both text and CAD data. It is engineered to embed within an organization's existing workflow, enabling engineers to resolve complex technical issues via natural language in real-time. Additionally, it identifies optimal parts from internal PLM systems, a library of over 100 million vendor components, and more than 1 million verified engineering sources.<ref name=":8"/>

Leo AI distributes its products through a network of value-added resellers (VARs) in multiple international regions, including the United States, Israel, the United Kingdom, India, Germany, Poland, France, and the [[Benelux]] region (Belgium, Netherlands, Luxembourg).<ref name=":6"/>

Operating within the software sector, the company focuses on engineering software, application integration, analytics, performance software, and multimedia graphics. Its primary technological competencies lie in cloud computing and artificial intelligence.<ref name=":3"/>

==History==
Founders Dr. Maor Farid and Mordechai (Moti) Moravia first crossed paths at age 18 while serving in the Brakim Program, an elite Israeli military track designed to train research and development engineers for the defense sector.<ref name=":6"/> Both founders earned their bachelor’s and master’s degrees in mechanical engineering, including research theses, from the Israel Institute of Technology (Technion) within an accelerated four-year period.<ref name=":9"/>

Driven by a shared enthusiasm for technology and innovation, both men excelled in the program. Following graduation, they entered the Israeli defense industry as engineers. Moravia spearheaded multidisciplinary engineering and AI development for the Merkava tank project. Meanwhile, Farid served as an AI researcher within Unit 8200 of the Israel Defense Forces, specializing in target recognition. His contributions to the field garnered national acclaim and were later highlighted by The Washington Post.<ref name=":9"/>

Despite their pride in national service, both engineers grew dissatisfied with the monotonous nature of their daily tasks. They found themselves spending weeks on manual processes, such as sourcing compatible parts, rather than engaging in creative design. They questioned why mechanical engineering lacked the automation and AI advancements that had already revolutionized electronics and software development.<ref name=":6"/><ref name=":9"/>

Upon completing his service, Farid traveled to Boston for a Fulbright postdoctoral fellowship at MIT, focusing his research on AI's application to mechanical design. Upon his return to Israel to teach at the Technion, he and Moravia resolved to execute their vision. Believing the technology was finally mature enough, they set out to construct an AI system capable of automating tedious mechanical design tasks, thereby freeing engineers to focus on problem-solving and creativity.<ref name=":9"/>

Prior to writing code, the founders interviewed over 900 mechanical engineers—ranging from junior staff to VPs of R&D—to pinpoint the most time-intensive aspects of their jobs. These insights formed the structural basis for Leo AI, the world's first AI copilot dedicated to mechanical engineering design.<ref name=":9"/><ref name=":10"/>

They developed a proprietary AI model named the Large Mechanical Model (LMM). In contrast to language models that output text, the LMM was engineered to comprehend technical documents, engineering assemblies, and CAD files. Trained on over 1 million engineering resources—including global standards, peer-reviewed literature, parts catalogs, and sketches—the model allows Leo to address mechanical queries with 95% accuracy (compared to 46% for GPT) and convert simple text prompts or sketches into detailed CAD models in seconds.<ref name=":6"/><ref name=":11"/><ref name=":12"/><ref name=":13"/>

To address enterprise security concerns regarding AI, Leo processes data within the customer’s existing infrastructure rather than transmitting it to external servers, thereby safeguarding intellectual property.<ref name=":13"/>

Leo AI was officially launched in May 2023,<ref name=":1"/> and incorporated in Delaware, USA, in November of that year.<ref name=":14"/> The company’s stated mission is to automate the routine 80% of engineering work, allowing professionals to dedicate the remaining 20% to innovation and building superior products.<ref name=":10"/><ref name=":15"/> It positions itself as a Large Mechanical Model created by mechanical engineers for the mechanical engineering community.<ref name=":9"/>

Within its initial months of operation, Leo attracted over 200,000 visitors and generated more than $100,000 in revenue without utilizing paid advertising.<ref name=":11"/><ref name=":12"/>

In February 2024, the company brought on Fielder Hiss, a former product leader at SolidWorks, as an advisor.<ref name=":16"/>

By June 2024, Saar Yoskovitz, Co-Founder and CEO of Augury, joined the advisory board to assist with enterprise growth and expansion.<ref name=":17"/>

In December 2024, a partnership was established with Visiativ, a prominent global engineering software reseller, to distribute AI-powered design tools to engineering teams.<ref name=":18"/>

Leo Ideation, an online module designed to gauge how engineers interact with AI tools, was released in February 2025. This feature enabled users to describe products in plain language, generating high-level summaries, technical documentation, and photorealistic concept images within five seconds. This tool allowed engineers to visualize concepts, create 3D mesh models, and expedite early design phases.<ref name=":19"/><ref name=":20"/>

In April 2025, Bertrand Sicot, former CEO of SolidWorks and Deputy CEO of Visiativ, was appointed to Leo AI’s Board of Advisors.<ref name=":21"/> That same month, the company introduced Windows directory integrations, enabling engineers to search and utilize internal documents and design files instantly. This capability allowed organizations to merge their proprietary knowledge bases with Leo’s AI, driving significant traction and adoption.<ref name=":22"/>

Dr. Farid presented the company's vision for AI-driven engineering at a joint conference with Visiativ Benelux in June 2025.<ref name=":23"/><ref name=":24"/> Simultaneously, training sessions were conducted for Visiativ’s team to facilitate the platform's introduction across the USA and Europe.<ref name=":25"/>

Also in June 2025, Leo AI collaborated with CoreTechnologie to integrate the 3D_Kernel_IO SDK. This integration enabled the platform to analyze and read 3D CAD data from major formats, including SOLIDWORKS, Creo, and NX.<ref name=":26"/>

July 2025 saw the formation of several strategic partnerships. The company teamed up with BEACON, a major Indian engineering software distributor, to launch AI design tools in India. Launch events in Mumbai, Pune, and Bengaluru drew hundreds of product developers and industry leaders, marking the company's entry into a rapidly growing market.<ref name=":27"/><ref name=":28"/>

During the same month, Leo AI partnered with Onshape to offer a cloud-native, AI-driven design workflow<ref name=":30"/> and collaborated with OpenBOM to create the first AI-powered Product Lifecycle Management (PLM) experience.<ref name=":29"/>

The company was also granted its first patent in July 2025 for a “Computerized System and Method for 3D CAD Design Generation.” This IP allows Leo to generate functional CAD assemblies from design goals, broadening design accessibility and reducing iteration times.<ref name=":31"/><ref name=":32"/>

A second patent was awarded in August 2025, protecting the system's ability to interpret CAD geometry, predict part compatibility, and automatically assemble components in a CAD environment.<ref name=":31"/><ref name=":33"/>

In August 2025, the company hosted a global webinar, “How Engineers Save Days with AI: Former SolidWorks CEO & Real Case Study.” The event featured John McEleney, co-founder of Onshape, alongside engineer Ashraf Serour, who showcased how Leo compressed a week-long design workflow into seven hours.<ref name=":34"/>

Leo AI secured $9.7 million in an oversubscribed seed funding round in September 2025. Led by Flint Capital, the round included participation from TechAviv, an a16z scout, OurCrowd, Two Lanterns VC, Mento VC, Prof. Yossi Matias (VP at Google), and Bertrand Sicot. This capital enabled international scaling, team expansion, and further refinement of the LMM for enterprise applications.<ref name=":6"/><ref name=":11"/>

Simultaneously, the company launched an AI onboarding assistant to help engineering teams access institutional knowledge via natural language.<ref name=":36"/> A major partnership with TraceParts was also announced, integrating over 2,100 supplier catalogs and 112 million certified parts directly into the Leo platform.<ref name=":37"/>

In October 2025, this collaboration expanded with the introduction of Free-Language Part Search. This feature allows engineers to request components using everyday language to receive instant supplier data, 3D previews, and CAD downloads. It is estimated to save up to 1,200 hours per engineer annually.<ref name=":37"/>

==Services==
Leo functions as a domain-specific AI system tailored for manufacturing and mechanical engineering. It operates on a patented Large Mechanical Model (LMM) that ingests an organization’s engineering data from text and CAD sources, validating it against over 100 million vendor parts and 1 million trusted engineering references.<ref name=":7"/><ref name=":8"/>

The LMM powers several core functions designed to enhance efficiency, problem-solving, and technical precision in product development.<ref name=":7"/>

By synthesizing reliable external sources with internal company data, Leo provides verified answers to engineering inquiries. This allows engineers to conduct structural analyses and complex calculations without the risk of broken links or misinformation. The system adapts responses to specific company workflows, aiding in error reduction, faster onboarding, and team consistency.<ref name=":7"/>

An engineering chat feature enables users to pose natural language questions regarding field work, workshop setups, or CAD models. Leo interprets the technical context to provide practical, situation-specific guidance.<ref name=":7"/>

The platform’s code solver executes advanced engineering computations by identifying appropriate formulas and retrieving accurate data. Useful for material selection, stress analysis, or mechanical design, it automatically references trusted sources, negating the need for spreadsheets or manual verification.<ref name=":7"/>

For multi-step mechanical problems or quick inquiries, the code interpreter offers verifiable, context-aware answers regarding mechanical principles, design trade-offs, coatings, and materials.<ref name=":7"/>

Leo also features a comprehensive part retrieval and component search system. Engineers can locate parts using specifications, images, or natural language. The AI scans internal PLM systems, online catalogs, and global vendor databases to identify the best matches, helping teams locate approved parts and existing designs to prevent redundancy.<ref name=":7"/>

The ideation capability assists in visualizing and brainstorming new concepts. By describing a product idea, engineers can rapidly generate documentation, explore alternatives, and create 3D models, effectively shortening the early design phase.<ref name=":7"/>

Leo integrates with major engineering platforms such as Teamcenter, Windchill, SolidWorks PDM, SOLIDWORKS, Onshape, and NX.<ref name=":38"/>

The AI embeds securely into Product Lifecycle Management (PLM) systems and engineering workflows. By surfacing valuable legacy knowledge, it helps teams increase profit margins, reduce lifecycle costs, and reuse proven designs.<ref name=":7"/>

Depending on reliable engineering sources and verified PLM data, the system speeds up decision-making and minimizes mistakes. Organizations leveraging Leo AI often see a return on investment within weeks due to significant time savings, improved design quality, and increased part reuse.<ref name=":7"/>

==Business==
Leo AI, Inc. maintains its headquarters in [[Cambridge, Massachusetts]], USA.<ref name=":14"/> In its initial month of monetization, the platform drew 200,000 visitors and generated over $100,000 in revenue without paid marketing campaigns.<ref name=":12"/>

Since launching, the platform has been adopted by over 57,000 engineers globally,<ref name=":10"/> facilitating the creation of more than 475,000 3D concepts in sectors including medical devices, transport, and aerospace.<ref name=":13"/>

Users report that Leo AI helps reduce design errors by 34%, boosts part reuse by 32%, and saves approximately 12 hours of labor weekly.<ref name=":8"/>

The company completed an oversubscribed seed funding round on September 2, 2025, raising a total of $9.7 million. The round was led by Flint Capital, with additional backing from Two Lanterns Venture Partners, TechAviv, OurCrowd, Mento VC, and an Andreessen Horowitz Scout.<ref name=":10"/><ref name=":11"/><ref name=":14"/><ref name=":38"/>

Prominent angel investors include Prof. Yossi Matias, Head of Google Research and VP at Google, and Bertrand Sicot, the former CEO of SolidWorks.<ref name=":10"/><ref name=":11"/><ref name=":14"/>

Analysts have pointed to the company’s strong investor backing and early adoption rates as indicators of market validation and rapid growth. Observers noted that the progress made between the initial funding in late 2023 and the 2025 seed round demonstrated substantial commercial traction.<ref name=":40"/> The participation of industry leaders like Matias and Sicot is viewed as a vote of confidence in the mission to modernize mechanical engineering via AI.<ref name=":6"/>

Sergey Gribov, a partner at Flint Capital, noted that information silos and poor coordination cause nearly half of all product delays and can raise manufacturing costs by 35%. He stated that Leo AI addresses these issues, potentially accelerating production and design processes by up to 70%.<ref name=":12"/>

==Leadership==
Dr. Maor Farid holds a degree from the Technion and completed a Fulbright postdoctoral fellowship at MIT in artificial intelligence and applied mathematics. He also participated in a Harvard University executive program. His background includes service as a commander and AI researcher in the Israeli Intelligence Corps (Units 81 and 8200) and as a Mechanical Engineer for the Israeli Prime Minister’s Office.<ref name=":2"/> He was named to the Forbes 30 Under 30 list in 2019 and founded the award-winning nonprofit “Learn to Succeed”.<ref name=":40"/>

Mordechai (Moti) Moravia is a Mechanical and Systems Engineer and AI expert. He graduated Summa Cum Laude with both B.Sc. and M.Sc. degrees from the Technion, where he participated in the elite Unit 81 “Brakim” program. He has led engineering and AI development for the Israeli Ministry of Defense, working on projects such as the Infantry Fighting Vehicle (IFV) and the Israeli Main Battle Tank (MBT).<ref name=":2"/>

==Clients==
Engineers and enterprises around the world utilize Leo AI. The platform has been integrated into workflows at companies including Bosch, Mobileye, Siemens, Scania, HP, Toyota, and Intel. It is also utilized by corporations such as Lockheed Martin, General Electric, LG, and Philips, as well as institutions like the Massachusetts Institute of Technology (MIT). Smaller firms, including SpaceIL, Tenova Advanced Technologies, ERC System, Elbit Systems, Toothsure, and Zutacore, also use the platform for analysis and design.<ref name=":7"/><ref name=":12"/><ref name=":13"/><ref name=":39"/><ref name=":41"/><ref name=":42"/>

==Intellectual Property & Compliance==
Leo AI was granted its initial patent (US Patent No. 18/907,937) in July 2025 for a “Computerized System and Method for 3D CAD Design Generation,” covering its AI-driven design generation method.<ref name=":32"/>

A second patent, “Method for Training AI Models to Generate 3D CAD Designs,” was granted in August 2025. This IP protects the company's method for training models to comprehend CAD geometry, automatically assemble components, and predict compatible parts within a CAD environment.<ref name=":31"/><ref name=":33"/>

The company adheres to rigorous compliance standards for system security and data protection. It holds SOC 2 Type II certification, confirming via independent audit that its internal controls meet standards for confidentiality, availability, and security. Additionally, Leo AI holds ISO certifications, meeting top-tier enterprise requirements for information protection.<ref name=":38"/>

To safeguard sensitive data, Leo AI employs end-to-end encryption throughout processing. The company enforces a strict no-data-reuse policy, ensuring that proprietary information remains the exclusive property of the user.<ref name=":38"/>

==Market Position==
Leo AI maintains a commercial presence in multiple global markets via a network of Value-Added Resellers (VARs). Distribution covers Israel, the Benelux region, Poland, Germany, France, India, the United Kingdom, and the United States.<ref name=":6"/><ref name=":40"/>

The technology serves diverse industries such as medical devices, industrial manufacturing, aerospace and defense, consumer electronics, high-tech, and automotive and transportation. It is extensively used in computer-related fields, lightning, industrial machinery, and robotics that rely on research and development.<ref name=":7"/><ref name=":13"/>

With the global mechanical engineering services market projected to surpass $620 billion by 2032, Leo AI is positioned to influence how physical products are developed and designed.<ref name=":12"/><ref name=":13"/>

==Technology==
The core of Leo AI is the Large Mechanical Model (LMM), an AI system engineered specifically for product design and mechanical engineering. It functions similarly to a Large Language Model (LLM) but processes mechanical data rather than text. Whereas LLMs utilize words as tokens, the LMM utilizes physical components—such as gears, bearings, and bolts—as its building blocks.<ref name=":11"/><ref name=":12"/>

The model interprets 3D CAD files, 2D images, sketches, and written requirements, understanding both real-world design constraints and the engineer's objectives.<ref name=":7"/> Trained on over 1 million engineering standards, professional articles, and textbooks, the LMM integrates seamlessly into CAD systems and existing workflows.<ref name=":39"/>

Leo AI constructs mechanical assemblies by analyzing constraints, standards, and geometry to instantly generate the correct component, demonstrating a comprehension of mechanical intent in the same way a language model forms sentences.<ref name=":10"/>

Adhering to Design for Manufacturing and Assembly (DFMA) standards,<ref name=":7"/> Leo AI ensures designs are viable for production in real-world scenarios. The technology connects with enterprise workflows and Product Lifecycle Management (PLM) systems, automating complex design steps to increase accuracy and speed while offering robust security for intellectual property.<ref name=":10"/>

==References==
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<ref name=":34">{{Cite web |url=https://leo-ai.discourse.group/t/leo-ai-webinar-august-how-en...eers-save-days-with-ai-former-solidworks-ceo-real-case-study/100 |title=Leo AI Webinar (August) How Engineers Save Days with AI: Former SolidWorks CEO & Real Case Study |website=Leo AI Community Announcements |date=August 2025 |access-date=2025-10-20}}</ref>
<ref name=":35">{{Cite web |url=https://leo-ai.discourse.group/t/leo-ai-s-new-feature-onboarding-support-using-free-language/105 |title=Leo AI's New Feature: Onboarding Support using Free Language |website=Leo AI Community Announcements |date=September 2025 |access-date=2025-10-20}}</ref>
<ref name=":36">{{Cite web |url=https://leo-ai.discourse.group/t/leo-ai-just-announced-a-partnership-with-traceparts/106 |title=Leo AI just announced a partnership with TraceParts |website=Leo AI Community Announcements |date=September 2025 |access-date=2025-10-20}}</ref>
<ref name=":37">{{Cite web |url=https://leo-ai.discourse.group/t/leo-ai-s-biggest-update-yet/107 |title=Leo AI's Biggest Update Yet |website=Leo AI Community Announcements |date=October 2025 |access-date=2025-10-20}}</ref>
<ref name=":38">{{Cite web |url=https://www.getleo.ai/blog/what-is-the-best-ai-for-mechanical-engineers |last=Farid |first=Maor |title=What Is the Best Al for Mechanical Engineers? |website=Leo AI Blog |access-date=2025-10-21}}</ref>
<ref name=":39">{{Cite web |url=https://pulse2.com/leo-ai-9-7-million-raised-for-transforming-mechanical-engineering/ |last=Chowdhry |first=Amit |date=2025-09-10 |title=Leo AI: $9.7 Million Raised For Transforming Mechanical Engineering |publisher=Pulse 2.0 |access-date=2025-10-21}}</ref>
<ref name=":40">{{Cite web |url=https://maorfarid.com/ |title=Dr. Maor Farid: Fulbright and ISEF Fellow at MIT Founder and CEO of Learn to Succeed |publisher=Massachusetts Institute of Technology |access-date=2025-10-21}}</ref>
<ref name=":41">{{Cite web |url=https://visiativ.co.uk/solutions/leo-ai/ |title=Leo AI Visiativ page |publisher=Visiativ |access-date=2025-10-22}}</ref>
<ref name=":42">{{Cite web |url=https://www.getleo.ai/customers |title=Leo AI Customers & Industry Leaders |website=Leo AI Blog |access-date=2025-10-22}}</ref>
}}

==External links==
*{{URL|https://www.getleo.ai/}} (official website)

[[Category:Companies]]

Leo AI - Revision history

imported>Ranarian: official website