Nominal, a Los Angeles-based software startup, raised US$75 million in a round led by Sequoia Capital with participation from Lightspeed Venture Partners and existing investors such as Lux Capital, General Catalyst, and Founders Fund.

Founded in 2022, Nominal builds software to help hardware makers test designs and track production, serving both federal agencies and private defense tech firms.

The company will use the funding to hire engineers and sales staff, enhance its products, and open a Washington office for better federal support.

Sequoia’s Alfred Lin will join Nominal’s board, highlighting the firm’s role in modernizing hardware development in defense, energy, and automotive sectors.

Nominal also plans to grow into robotics and consumer electronics by expanding its customer base.

🔗 Source: Bloomberg

🧠 Food for thought

1️⃣ Defense tech funding surge reflects changing investment appetites

Nominal’s $75 million funding round mirrors the broader defense tech sector’s momentum, which attracted $3 billion in 2024, an 11% increase from the previous year 1.

This growth is part of a significant shift in venture capital attitudes, with defense tech startups increasingly viewed as viable investments despite historically high barriers to entry and atypical costs 2.

The sector’s appeal has grown significantly, with leading companies in the space collectively valued at over $45 billion and having raised nearly $10 billion 3.

This trend extends beyond purely military applications, as Nominal’s expansion into robotics, energy, and automotive industries demonstrates the growing convergence between defense innovation and broader industrial applications.

Sequoia’s involvement signals how mainstream venture capital has embraced this previously overlooked sector, with former Pentagon officials increasingly transitioning into venture capital roles to bridge traditional gaps between Silicon Valley and defense 2.

2️⃣ Hardware development faces unprecedented data challenges

Nominal addresses a critical and growing problem: modern hardware generates vastly more data than traditional engineering tools can effectively process.

This aligns with documented examples in aerospace where a single jet engine can generate 10 GB of data per second from over 5,000 sensors—an overwhelming amount of information that requires specialized software to interpret 4.