Axelera Secures $68M Series B Funding
Axelera AI closed a $68 million Series B round this week, lifting total capital raised to $120 million. The round attracted the European Innovation Council Fund, Innovation Industries Strategic Partnership Fund, Invest-NL and Samsung Catalyst Fund. The backing lands as the generative AI boom keeps demand for purpose-built silicon running hot, and as larger players from SoftBank to OpenAI test their own plays in chips.
Fabrizio Del Maffeo, co-founder and CEO, told TechCrunch the raise is about matching performance with cost. “There’s no denying that the AI industry has the potential to transform a multitude of sectors,” he said. “However, to truly harness the value of AI, organizations need a solution that delivers high-performance and efficiency while balancing cost.” That framing has been Axelera’s pitch for a while now, and it’s the reason the company has stayed focused on edge rather than chasing training clusters.
Headquartered in the Netherlands, Axelera runs a roughly 180-person team spread across Belgium, Switzerland, Italy and the U.K. It designs AI-running chips and systems for security, retail, automotive and robotics, and sells to partners building B2B edge computing and internet of things products. The company says it has “tens” of enterprise customers. That narrow but steady base is what the new money is meant to widen.
Metis Platform Enters Volume Production
The Series B is timed to the ramp of Axelera’s flagship Metis AI platform. Del Maffeo said Metis entered full production in Q2 and will be delivered in volume in Q3. The new cash will fund expansion ahead of full production in H2 2024, and support a next product family aimed at computer vision, large language models and large multimodal models.
“Axelera AI is now developing a new generation of products for computer vision, large language models and large multimodal models. This new product family will be unveiled later this year and enter in full production in 2025,” Del Maffeo said. The timeline matters because Metis is the proof point for the company’s hardware-software approach. Axelera has tried to differentiate by shipping both chip hardware and software to manage and deploy AI models to that hardware. From the outside, the bet looks to be working, at least enough to close a sizable B round.
The company also has preliminary plans to fund R&D for chips aimed at high-performance compute use cases. That is a clear step toward data centers, a market it has so far mostly avoided. Del Maffeo described the mission as democratizing access to AI, from the edge to the cloud, and said expanding product lines beyond edge will let Axelera address industry challenges in AI inference and support current and future processing needs.
RISC-V and In-Memory Architecture
Axelera’s hardware stack is defined by two choices: RISC-V as the instruction set architecture and in-memory computing. ISAs are the technical spec at the foundation of chips that describe how software controls hardware. Most designers license from Arm or Intel. RISC-V is open and royalty-free, which reduces lock-in and gives customers flexibility.
In-memory computing means running calculations in a system’s RAM to cut the latency introduced by shuttling data to and from storage. The appeal is obvious for inference at the edge, where power budgets are tight and responsiveness matters.
Axelera isn’t alone. NeuroBlade is developing chips that combine compute and memory into a single hardware block for data processing. MemVerge, GigaSpaces, Hazelcast and H20.ai also offer in-memory hardware solutions for AI and data analytics. Tenstorrent, backed by Hyundai Motor Group and Samsung, sells AI processors and related IP built around RISC-V. The field is crowded, and most rivals have deep pockets.
Market Heat and Competitive Reality
The AI chip market is heating up fast. According to Statista and Market.us data, revenue could reach as much as $67 billion by 2027. Nvidia commands an estimated 70% to 95% share of the AI chip market per Mizuho Securities. That dominance makes it an almost immovable object, but it also creates room at the margins for specialized players.
VC money is flowing in volume. A Crunchbase report from June found VC-backed chip startups have raised nearly $5.3 billion across 175 deals so far this year. The generative AI boom is driving demand for chips purpose-built to train and run generative models, and major players are scrambling for position. SoftBank’s Masayoshi Son is reportedly looking to raise $100 billion for a chip initiative that would compete with Nvidia. OpenAI is said to be in talks with investment firms to launch an AI chip-making venture.
Axelera has kept a comparatively low profile relative to those moves. Its niche is chips that run AI on edge devices, a segment where power efficiency and cost control outweigh raw throughput. It was born out of an effort led by Del Maffeo and a group at Imec, the Belgium-based technology lab, along with Evangelos Eleftheriou and a group of Zurich-based IBM researchers to build a highly efficient AI chip architecture. The founding team incubated much of Axelera within Bitfury Group, a blockchain company specializing in Bitcoin hardware.
Workforce, Customers and Positioning
With about 180 people across four countries, Axelera is still a relatively small operation. It designs for applications where latency and privacy matter: security cameras that can identify threats locally, retail analytics that run in stores without constant cloud uplinks, automotive systems that need real-time decisions, and robotics that can’t afford round trips to a data center.
The company’s target markets are clearly edge-first, but the data center interest signals a pivot. Shipping chips at scale is the real challenge. Competing against countless others in the AI chip race, many with formidable backing, will test whether the hardware-plus-software strategy and the RISC-V, in-memory design choices translate into design wins.
Del Maffeo is candid about the odds. Axelera has little chance of unseating entrenched vendors like Nvidia anytime soon, if ever. But nabbing even a fraction of a $67 billion market would be a meaningful win. For now, the company is focused on executing the Metis ramp, unveiling the next product family for computer vision and LLMs, and using the $68 million to broaden from the edge outward.
The funding supports the stated mission to democratize access to AI, from the edge to the cloud. Whether that expansion holds up against the capital pouring into the sector is the open question Axelera will have to answer in the next production cycles.
