Discover 5 Top Machine Learning Startups impacting Engineering

Curious about new technological advancements in the engineering industry? Explore our analysis of 430 global machine learning (ML) startups & scaleups and learn how their solutions impact your engineering business!

Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the engineering sector. This time, you get to discover five hand-picked machine learning startups impacting engineering.

Out of 430, the Global Startup Heat Map highlights 5 Top Machine Learning Startups impacting Engineering

The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering 2 093 000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.

The Global Startup Heat Map below reveals the distribution of the 430 exemplary startups & scaleups we analyzed for this research. Further, it highlights five machine learning startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these five startups & scaleups in this report. For insights on the other 425 machine learning solutions for engineering, get in touch with us.

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Photoruction provides Construction Engineering Assistance

Founding Year: 2016
Location: Tokyo, Japan
Funding: USD 9,7 M
Use this solution for Construction Defect Detection

Photoruction is a Japanese startup that offers AOZ Cloud, a cloud-based ML engine to assist construction engineering. It allows engineers to analyze images from a construction site and receive updates on the construction progress and bottlenecks. The engine also enables engineers to share building drawings and extract details such as room dimensions automatically. Furthermore, it enables construction managers and engineers to inspect for defects by analyzing daily report data using natural language processing (NLP). Photoruction thus streamlines the construction process and improves operational efficiency.

Renumics offers Automated Engineering Workflows

Founding Year: 2017
Location: Karlsruhe, Germany
Funding: USD 29 500
Collaborate with Renumics for Engineering Process Digitization

German startup Renumics combines machine learning and AI to digitize engineering processes and workflows. The startup’s platform automates geometry preparations, component segmentation, and grid generation to simulate product designs. It also enables engineers to explore their designs and problem space through 3D visualizations that assist in identifying correlations and outliers. Renumics enables small- and medium-sized engineering companies to create data-driven product simulations and improve product development.

Secondmind enables Sustainable Automobile Engineering

Founding Year: 2017
Location: Cambridge, UK
Funding: USD 34 M
Partner with Secondmind for Data-driven Car Design

UK-based startup Secondmind leverages machine learning to engineer and design cleaner cars. The startup’s platform offers advanced digital modeling features for automobile manufacturers to create data-driven car designs. It also features experimenting and simulating modules to test the performance of model designs and identify vehicle parameters such as emissions levels. As a result, Secondmind enables automobile manufacturers to reduce complexities associated with engineering designs as they transition towards electric vehicles (EVs).

SimpleMachines facilitates Hardware Designing

Founding Year: 2016
Location: San Jose, USA
Funding: USD 19 M
Use this solution for Data-Intensive Application Development

SimpleMachines is a US-based startup that develops an AI- and machine learning-enabled platform to optimize hardware-software compatibility. It allows software engineers to improve the performance of their data-intensive AI applications by reconfiguring the underlying hardware using a novel compiler. This compiler intelligently composes programs to match the compatibility of the hardware after its analysis. Based on this, the actual hardware is then modified physically to ensure seamless integration of the application. This allows engineers to develop smart compatible applications & hardware tailored to specific computing needs across industries like automotive, financial services, and manufacturing.

Manceps offers Automated Product Development

Founding Year: 2017
Location: Portland, USA
Reach out to Manceps for Budget-based Design

Manceps is a US-based startup that uses AI and ML for product design and development. The startup’s software allows product designers to develop iterative novel designs based on customer feedback. It also enables design teams to accurately predict the scope and budget of their projects, thereby optimizing resource utilization and improving overall productivity. Furthermore, Manceps automates debugging during product development which leads to safer products and lowers human errors. This enables engineering companies to improve product reliability and reduce time-to-market.

Discover more Engineering Startups

Engineering startups such as the examples highlighted in this report focus on robotic process automation (RPA), automated product design, sustainable engineering, and high-computing hardware. While all of these technologies play a major role in advancing the industry, they only represent the tip of the iceberg. To explore engineering solutions in more detail, let us look into your areas of interest. For a more general overview, download one of our free Industry Innovation Reports to save your time and improve strategic decision-making.

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