Led · Seed · Aug 2026

Zerolook uses machine-learning models trained on historical fares, schedules and availability to predict flight options and prices, returning each prediction with a confidence score. The product sacrifices some real-time accuracy in order to answer far larger volumes of search queries at lower cost compared with live pricing systems. The founders—Simone Lini (ex-Google Flights/Waynaut) and George Hadjiyiannis (PhD, MIT; ex-Kayak/Google/Nvidia/eBay)—intend to validate the approach through pilot programs with online travel partners. Zerolook plans to launch its first API and expand its machine-learning team in Zurich using proceeds from the pre-seed round. The company cites industry trends—searches per ticket sold rising from hundreds to tens of thousands and projected to reach millions by 2030—that drive demand for lower-cost search infrastructure. It operates in a market for flight data APIs valued at $1.72 billion in 2025 and projected to grow to $4.67 billion by 2033, and the pilots are intended to determine whether predictive pricing is sufficiently accurate for airlines and OTAs.

Led · Seed · Aug 2026

Exclaim Robotics develops mobile robots that autonomously navigate data halls, access rack fronts and perform hands-on maintenance tasks inside live server racks. Its initial scope focuses on narrow, high-frequency interventions such as cleaning and replacing fibre-optic connectors and SFPs, handling copper cabling, and swapping failed drives. The company emphasizes operating safely inside live 800-volt racks and aims to reduce labour-intensive manual maintenance while improving operational efficiency for data centre operators. Founder Helen Oleynikova, who has prior robotics experience at Google, Microsoft, Nvidia, Willow Garage and ETH Zürich, leads the team alongside founding engineer Patrick Pfreundschuh, with two more founding engineers planned to join in 2027. Exclaim has positioned itself alongside startups such as Boost Robotics, Watney Robotics and Gecko Robotics in the data-centre robotics market and has stated goals of accelerating product development using its recent funding.

Participated · Series B · Jul 2026

Qureight provides two integrated products for pharmaceutical clinical trials: Workflow, which speeds imaging decision turnaround from about two weeks to 48 hours, and AI Lung, which constructs detailed models of airways and blood vessels from chest scans. The company has built a general-purpose foundation model of the chest that enables development of disease-specific deep learning models in one to two months. Qureight is running global clinical trials with partners including AstraZeneca, Bristol Myers Squibb, and several biotech firms. Founded in 2018, the company combines clinical leadership—co-founder and CEO Dr Muhunthan Thillai continues clinical work—with a senior technical team recruited from industry and academia. Financially, Qureight has raised a £1.5 million seed in 2022 and the recent $20 million Series B to support lab build-out, therapeutic-area expansion, and headcount growth.

Participated · Series A · Jun 2026

Founded in 2021, Astral Systems designs and operates compact multi-state fusion (MSF) reactors to generate high-intensity neutron beams for manufacturing medical isotopes. The company currently operates reactors at TRL9, runs three commercial fusion facilities, and has signed research contracts that have generated more than £3M in revenue. Astral has partnered with McMaster University and Brazil’s Institute for Energy and Nuclear Research to produce isotopes including Actinium-225 and Lead-212, and plans to bring at least one isotope to market by early 2027. With the Series A financing, Astral intends to build out next-generation reactors at the former Berkeley Power Station, expand its headcount from 23 to more than 40 by end-2026, and target profitability in 2027. The firm positions its modular MSF design as able to produce a broader range of isotopes than single-purpose competitors.

Led · Seed · Jun 2026

Wassist builds a no-code platform that automatically creates brand-trained AI assistants on WhatsApp by ingesting a store URL and integrating with e-commerce tools like Shopify, Klaviyo, Recharge, and Yotpo. Its agents can answer product questions, recommend items, recover abandoned carts, handle order updates, and keep the purchase flow inside the chat thread. The company was founded in 2025 by Josh Warwick, who developed the product during weekend hackathons and grew usage from about 2,000 to over 80,000 customer conversations without paid marketing. Wassist recently made its first hire and was selected for Balderton Capital’s Launched programme. The startup positions WhatsApp as a primary commerce channel and plans to use its new pre-seed funding to accelerate product development and expand the platform’s no-code capabilities. The articles do not report revenue figures or prior institutional funding.