Who Is Hugo Nordell? Encube, Funding, AI Strategy & Vision

Artificial intelligence has transformed software development, content creation, and customer service over the past few years. Now, a new wave of startups is bringing AI into industries where engineering expertise and complex product design have traditionally relied on manual processes.

One of these companies is Encube, a Stockholm-based startup led by Hugo Nordell, whose mission is to help engineering teams design better physical products with the support of AI.

Unlike general-purpose AI assistants that focus on writing code or generating text, Encube is building AI specifically for hardware engineering. Its platform helps engineers collaborate, evaluate manufacturing constraints, and make smarter design decisions before products reach production.

As manufacturers face increasing pressure to reduce development time and costs, AI-powered engineering platforms like Encube are becoming an important part of digital transformation. According to McKinsey & Company, generative AI could create trillions of dollars in annual economic value across industries, with engineering, manufacturing, and product development among the sectors expected to benefit from improved productivity and faster decision-making.

In this article, we'll explore who Hugo Nordell is, what Encube does, its funding journey, AI strategy, and why the company is gaining attention in the industrial AI space.

Who Is Hugo Nordell?

Hugo Nordell is the co-founder and CEO of Encube, a Swedish technology company developing AI-powered software for hardware engineering teams.

Before launching Encube, Nordell worked closely with industrial software and manufacturing technologies. Through this experience, he recognized that hardware engineering workflows remained fragmented compared to modern software development. Engineering teams often relied on disconnected CAD tools, manual reviews, spreadsheets, and siloed knowledge, making collaboration slower and increasing the likelihood of costly design revisions.

Together with co-founder Johnny Bigert, Nordell founded Encube in 2021 with the goal of bringing AI into hardware engineering. Rather than replacing engineers, the company aims to provide intelligent software that helps teams make informed decisions throughout the product development lifecycle.

Nordell has consistently emphasized that AI should augment engineering expertise by reducing repetitive tasks, improving collaboration, and surfacing manufacturing insights earlier in the design process.

Johnny Bigert and Hugo Nordell, Cofounders of Encube

What Is Encube?

Encube is an AI-powered engineering platform designed for companies developing physical products.

The platform enables engineering teams to collaborate around CAD models, technical drawings, manufacturing information, and product knowledge within a shared workspace.

Its capabilities include:

• AI-assisted engineering workflows

• Browser-based CAD collaboration

• Design review and commenting

• Engineering knowledge management

• Manufacturing-aware design analysis

• Product documentation

• Cross-functional collaboration

Unlike traditional engineering software that primarily focuses on creating geometry, Encube aims to provide engineering intelligence throughout the product development process.

The company's mission is simple:

Help engineers build better products faster while reducing manufacturing complexity, redesign costs, and time to market.

The Challenge Encube Is Solving

Although manufacturing technology has advanced significantly, hardware engineering workflows often remain disconnected.

Many engineering organizations still use separate tools for:

• CAD design

• Manufacturing planning

• Quality assurance

• Supplier communication

• Product lifecycle management (PLM)

• Technical documentation

As information moves between different systems, important manufacturing considerations may only emerge after designs are nearly complete. This can lead to expensive redesigns, production delays, and increased development costs.

Industry research consistently shows that decisions made during the design phase have a major impact on overall manufacturing costs. Engineering teams that identify manufacturability issues early can significantly reduce downstream expenses and improve product quality.

Encube addresses this challenge by integrating AI-driven insights directly into engineering workflows, helping teams evaluate designs before they reach production.

Hugo Nordell's Vision for AI in Hardware Engineering

Nordell believes AI should serve as an engineering partner rather than a replacement for engineers.

His vision centers on giving engineering teams access to intelligent tools that understand product development, manufacturing constraints, and design trade-offs.

Instead of generating designs without context, Encube focuses on helping engineers answer practical questions such as:

• Can this part be manufactured efficiently?

• Will this design increase production costs?

• Are there simpler alternatives?

• What design changes could improve manufacturability?

• How can engineering knowledge be shared across teams?

This approach reflects a broader industry trend toward domain-specific AI systems that combine large language models with specialized engineering knowledge.

Encube's AI Strategy

Encube is developing AI specifically for hardware product development rather than adapting general-purpose AI models.

Its strategy focuses on embedding engineering intelligence into everyday workflows.

Manufacturing-Aware AI

The platform analyzes designs while considering manufacturing constraints, enabling engineers to identify potential production challenges much earlier.

AI-Assisted Collaboration

Engineering teams can review CAD files, drawings, comments, and documentation within a collaborative environment instead of relying on multiple disconnected systems.

Knowledge Capture

Engineering expertise often exists within individual teams or experienced employees. Encube aims to preserve and organize this knowledge so it can be reused across future projects.

Intelligent Design Reviews

Rather than manually checking every design iteration, AI helps engineers identify potential issues and focus their attention where it matters most.

Agentic Engineering: Moving Beyond AI Assistants

One of the concepts discussed by Encube is Agentic Design Engineering.

Unlike traditional AI assistants that respond to prompts, agentic AI systems can reason through engineering tasks, evaluate multiple design alternatives, and iteratively improve solutions while keeping engineers in control.

Although this technology is still evolving, it represents an important shift in how AI may support engineering teams in the future.

Encube's $23 Million Funding

Encube operated largely in stealth mode before announcing its public launch alongside a $23 million funding round.

The investment was led by Kinnevik, with participation from Promus Ventures and Inventure, providing the company with resources to expand its engineering platform, grow internationally, and accelerate AI research.

The funding will support:

• Product development

• AI research

• Team expansion

• European growth

• North American market expansion

The investment highlights growing confidence among venture capital firms in AI applications built specifically for industrial engineering rather than general consumer use.

Customers and Industry Partnerships

Encube has collaborated with several industrial organizations during product validation, including companies in automotive, manufacturing, and industrial automation.

These collaborations allow the platform to address real-world engineering challenges while refining AI models using practical manufacturing workflows.

Working alongside established manufacturers also helps ensure that AI recommendations align with actual production requirements rather than theoretical design principles.

Why Investors See Potential in Encube

Industrial engineering represents one of the largest untapped opportunities for AI adoption.

While software developers have rapidly embraced AI coding assistants, hardware engineers have had fewer specialized AI tools available.

Investors see several factors driving demand:

• Increasing product complexity

• Global engineering collaboration

• Manufacturing cost pressures

• Engineering talent shortages

• Faster product development cycles

• Digital transformation initiatives

According to IBM, AI is becoming increasingly important in manufacturing as organizations seek to improve operational efficiency, automate repetitive work, and enhance decision-making across engineering and production teams.

How Encube Differs from Traditional CAD Software

Rather than replacing CAD software, Encube complements existing engineering tools by adding collaboration and AI-powered decision support.

The Growing Role of AI in Engineering

The engineering industry is undergoing a major digital transformation.

According to McKinsey, AI has the potential to improve productivity across product development by reducing repetitive work, accelerating knowledge discovery, and supporting better decision-making.

Similarly, manufacturers are investing in digital engineering platforms that connect design, simulation, collaboration, and production planning into unified workflows.

As AI models become more specialized, companies like Encube are demonstrating how industry-specific AI can solve problems that general-purpose AI cannot.

What's Next for Encube?

Following its funding round, Encube plans to continue expanding its platform while investing heavily in AI research and international growth.

Future priorities include:

• Expanding engineering AI capabilities

• Supporting larger enterprise customers

• Enhancing collaborative workflows

• Improving manufacturing intelligence

• Advancing agentic engineering systems

If successful, Encube could become an important software platform for engineering organizations seeking to modernize product development with AI.

Final Thoughts

Hugo Nordell is part of a growing group of entrepreneurs applying artificial intelligence to highly specialized industries.

Rather than building another general AI assistant, he is focused on one of manufacturing's biggest opportunities: helping engineers design better products through AI-powered collaboration and engineering intelligence.

With strong investor backing, an ambitious vision, and growing industry interest in manufacturing AI, Encube is positioning itself at the intersection of artificial intelligence, engineering, and industrial innovation.

As hardware companies continue their digital transformation, platforms like Encube may play a significant role in shaping how physical products are designed, reviewed, and manufactured in the years ahead.