Swedish startup Endra has secured a significant $20 million seed funding round to advance its AI-powered platform for building design. Led by Notion Capital, the investment aims to accelerate the automation of Mechanical, Electrical, and Plumbing (MEP) engineering. The company's technology addresses long-standing inefficiencies in the construction sector, promising to drastically reduce project timelines and boost productivity for engineering teams.
Addressing Industry-Wide Inefficiencies
The global built-environment sector faces immense pressure to expand its delivery capacity to meet soaring demand. Projections indicate a need for substantial growth in construction output, extensive retrofitting of existing buildings for sustainability, and millions of new homes annually. This surge in requirements, coupled with the expansion of digital infrastructure like data centers, strains traditional engineering workflows.
For decades, the MEP design process has remained a highly manual and laborious task, often creating a significant bottleneck in building projects. Skilled engineers can spend weeks or months using computer-aided design software to complete complex system layouts. This antiquated process has seen little technological advancement for over 25 years, leaving it ripe for disruption and innovation.
An AI-Powered Solution for MEP Design
Endra's platform directly confronts these challenges by automating the end-to-end MEP design workflow. Engineers can import an architect's 3D model, and the system automatically generates building-code-compliant designs for electrical, lighting, and fire alarm systems. The company plans to expand its capabilities to include HVAC and plumbing systems within the next year.
The technology is a hybrid system combining large language models with proprietary 3D simulation and deterministic algorithms. LLMs are utilized to interpret the architect's intent and identify key design parameters from building specifications. This information then feeds into a unique geometry engine that optimizes system layouts while ensuring regulatory compliance across different regions.
The results reported from deployed projects are dramatic, with efficiency gains exceeding 70 times that of traditional methods. For instance, designing the electrical system for a large commercial building can be reduced from two months to under 24 hours. This acceleration allows engineering teams to deliver complex projects with far greater speed and predictability.
Fueling Global Expansion and Growth
The $20 million seed round, one of the largest for a Swedish company to date, was led by Notion Capital with participation from Norrsken VC. This new investment follows a successful €3 million pre-seed round, providing substantial capital for the company's ambitious growth strategy. The funding underscores investor confidence in Endra's mission to modernize the engineering design industry.
With the fresh capital, Endra plans to triple its team size over the next six to twelve months to support its rapid scaling. A key part of its strategy involves establishing offices in the United States, the United Kingdom, and Germany. This international expansion will enable the company to better serve its growing global customer base.
Market reception for Endra's platform has been overwhelmingly positive since its launch with initial customers in August. The company has already accumulated a waiting list of over 600 firms from more than 90 countries. This strong demand highlights the urgent need within the construction industry for solutions that address labor shortages and productivity stagnation.
Endra's successful funding round and innovative technology position it as a key disruptor in the MEP engineering space. By automating complex design work, the company is not just accelerating project timelines but also empowering engineering firms to meet the escalating demands of the modern world. As Endra expands its global footprint, its AI-driven platform is set to redefine efficiency and productivity standards across the construction industry.

