Due to the exponential growth of artificial intelligence in recent years, many types of AI chips have emerged, designed to solve various tasks. The company Olix has raised $312 million with the goal of creating a single chip capable of processing all stages of an AI model's operation.
As a result of this round, the company's valuation grew to $3.3 billion, which is three times higher than the approximately $1 billion mark Olix reached just six months ago after raising $220 million.
Olix was founded by James Dockomb in London in 2024 when he was young, after having created a previous company specializing in brain monitoring technologies. Dockomb argues to investors that universal chips from Nvidia are reaching the limits of their capabilities.
According to Dockomb, a data center performing AI inference is essentially a token-generating factory, and each such token requires hundreds of different operations. However, most companies continue to perform all these operations on the same chip.
Olix's solution is the development of the X-1 chip, which distributes the model's workload across multiple chips instead of limiting the work of a single processor. These chips communicate with each other using light rather than copper wires, which, according to Olix, reduces latency and power consumption.
The company's first chip, DX-1, is responsible for the decoding stage—the moment when the model actually generates its output. In the modelPlus with 100 billion parameters, the company claims it can generate over 10,000 tokens per second per user while using less energy than a standard chip of the same size.
Olix asserts that the same architecture is designed to scale up to models with 10 trillion parameters or more. An important aspect of the design is that Olix avoids using advanced packaging and high-bandwidth memory, as these are two components with limited supply in the current chip industry. This conscious decision is aimed at avoiding the same supply queues as everyone else chasing Nvidia.
Thanks to the capital raised, Olix hired two experts: Matt Bryers and Nick MacQueen, who now join the board of directors. Bryers previously worked as CFO at Wise, and MacQueen is known for his co-authorship of software-defined networks and OpenFlow. This indicates that the founder is very meticulous about the scaling issue.
Olix is not the only startup aiming to capitalize on this opportunity. Fractile from Bristol managed to raise $220 million in May with support from Accel and Founders Fund. At these figures, Olix's $3.3 billion valuation, even after tripling in six months, appears to be a smaller player in the market.
The AI chip industry is already valued at $84 billion, and the market is projected to more than triple by 2030. There is huge demand and a strong reason to pay attention to Olix. The company currently has over 140 employees working in London, Bristol, Toronto, Austin, and San Francisco.
The company plans to make DX-1 available to customers in the second half of 2027. How well the claimed throughput metrics match reality outside of presentations will matter much more than the size of the current round.
The industry is showing increased interest in chip speed, but significant performance losses occur in the interaction between the chips themselves. In dense artificial intelligence clusters, GPUs often operate at only 30–40% capacity, meaning that most of the time powerful chips are idle waiting for data rather than processing it.
The startup Eliyan, which has received support from Cisco, raised $145 million with a company valuation of one billion dollars to address this issue. As cluster sizes increase, data transfer speed becomes insufficient. Simply increasing data volume through conventional copper wires leads to increased power consumption, heat generation, and ultimately, slower chip operation. Eliyan offers a solution to this problem.
Eliyan does not manufacture the chips itself; instead, it creates the connections between them. Founded in Santa Clara by Ramin Farjadrad, Patrick Soheil, and Cyrus Ziae, the company uses its NuLink PHY cores to move data between crystals on the same package and between separately packaged chips. Its NuGear chiplets are responsible for memory scaling and inter-rack scaling.
The most critical aspect for chip manufacturers is packaging. Many competing methods require the use of expensive silicon interposers to achieve high throughput. Eliyan's chiplets achieve comparable metrics using standard organic substrates, allowing chip designers to increase throughput without completely redesigning the chip's physical layout.
The funding round was led by Seligman Ventures, and Seligman Managing Partner Umesh Padwal joined Eliyan's board of directors. He was previously a member of the Mellanox board before its acquisition by Nvidia for $6.9 billion, an event that changed the industry's perception of networking technologies. Cisco and Lumentum are new strategic investors: Cisco has a division specializing in optics and silicon, and Lumentum manufactures lasers and optical modules that hyperscale data centers will purchase. In addition to these, Eliyan has received support from several leaders in the chip industry.
Prior to this round, Eliyan had investments from AMD, Arm, Meta, Coherent, Intel Capital, and Samsung Catalyst Fund. Investors who invest at such early stages typically aim to participate in shaping future technologies rather than just seeking profit. The company stated that it plans to begin shipping its first chiplets later this year and expects to reach hundreds of millions of dollars by 2027. Furthermore, the company holds over 100 patents.
Eliyan's main bet is that interconnectivity is the bottleneck for chiplets, and the company owns the intellectual property to solve it. This gives it an advantage over major players like Nvidia and Intel, who are beginning to focus on the same problem. The next phase of the AI race will be determined not by who releases the fastest chip, but by who can move data across the entire warehouse of such chips without exceeding the power budget, and it is in this race that Eliyan attracted $145 million.
The tech startup Genius AI has raised $44 million in investment to capitalize on the growing demand in the personal interaction-focused service economy. With this Series D funding round, the company's valuation reached $1.15 billion.
Venture firm Lux Capital led the round. Other investors included Bessemer Venture Partners, Imaginary Ventures, L Catterton Growth, 2048 Ventures, and StepStone Private Ventures. These funds will allow Genius AI to shift its focus from beauty booking software to autonomous artificial intelligence tools for a wider range of in-person services.
The company, formerly known as GlossGenius, was founded in 2015 by identical sisters Danielle and Leah Cohen-Shohet. They initially created GlossGenius to help salon owners, aestheticians, and spa operators manage their daily operations. Danielle independently learned programming and wrote the initial code, and over time, the software became a dominant force in the market, helping small businesses process payments, book clients, and promote their services.
The company is now changing its name to Genius AI, signifying a broader mission. As Genius AI, the platform will support all in-person professionals. It is planned for use in medical spas, physical therapy centers, fitness studios, injections, and health clinics.
The physical service economy in the United States includes about eight million businesses generating over $2 trillion in annual consumer spending. Although studies show that business owners spend nearly 36% of their working time on administrative tasks, Genius AI aims to completely eliminate this bureaucratic burden. The platform goes beyond simple assistance tools and transforms into an autonomous AI agent capable of handling complex tasks end-to-end, freeing up business owners to interact with clients.
The company demonstrates impressive growth and operational scale. Currently, the system is used by over 125,000 businesses across half of the US zip codes. Genius AI reports that its platform is approaching $200 million in annual revenue. To date, the company's tools have helped clients save over 112 million hours of administrative work. To deepen penetration into the healthcare sector, the company has added full HIPAA compliance, allowing physical therapists and clinical specialists to securely store sensitive patient data. This gives Genius AI a significant advantage over traditional tools lacking privacy protection. As artificial intelligence automates office work, human care becomes even more valuable, as skilled professionals like masseuses and trainers provide care that computer code cannot replicate. The new funding is planned to be used to expand software development and increase the engineering team.
