TL;DR
London-based semiconductor startup Olix has raised $220 million at a valuation just over $1 billion to develop AI chips that challenge Nvidia’s dominance. Founded in 2024 by 25-year-old James Dacombe, the company is building an optical digital processor targeting the growing demand for AI inference.
A new approach to AI silicon
Rather than adapting Nvidia’s GPU architecture, Olix says it is building a “new class of accelerator” designed for high performance and “free from the architectural and supply chain constraints” of current AI processors. The company is developing an optical digital processor with a novel memory and interconnect architecture that remains compatible with existing AI models.
The latest $220 million round was led by London-based Hummingbird Ventures, whose previous investments include Revolut and Deliveroo. Other backers include Plural, Vertex Ventures, LocalGlobe, and Entrepreneurs First, bringing total financing to $250 million.
Jonathan Heiliger, general partner at Vertex Ventures and a former Facebook infrastructure executive, said: “Today’s GPU-based approach forces a compromise between speed and cost. Olix is taking a radically different approach designed to deliver a step change in both.”
UK chip ambitions
Olix — recently renamed from Flux Computing — hopes to deliver its first products to customers as soon as next year. UK investors see the company as a potential foothold in a market dominated by US players.
However, UK financing for chip companies still lags behind Silicon Valley. California-based Cerebras recently announced a $1 billion raise at a $23 billion valuation. SoftBank owns Arm and acquired Bristol-based Graphcore in 2024.
Another British AI chip startup, Fractile, announced plans to invest £100 million to expand its London and Bristol facilities, as AI minister Kanishka Narayan urged UK entrepreneurs to “embrace risk” and back “homegrown” innovation.
Looking forward
No startup has yet significantly loosened Nvidia’s grip on the AI chip market. But with inference costs becoming a major concern for companies running large AI models, there is clear investor appetite for alternative approaches — particularly from companies offering fundamental architectural innovation rather than incremental improvements.