Q1 2026 Results

About SuperSeed Capital Limited

SuperSeed exists to back Europe's best B2B SaaS founders at the earliest stages and to help them build great companies. In the short term, our portfolio companies enable their customers to drive revenue growth and efficiency savings using next-generation software and AI. In the long-term, they have an opportunity to create category defining global technology companies. SuperSeed focuses on the fundamentals by helping founders build good companies with strong unit economics and sensible distribution models.

Forward-looking statements

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Investment Manager's Review

Where the AI economy is, and where venture lives

In Q1, Alphabet alone spent more on capital infrastructure than the entire European venture capital industry invested across all of its startups in the same quarter. $35.7 billion against $17.6 billion. We are not in the same business.

The same quarter, Alphabet issued a 100-year sterling bond, the first century bond by a technology company since Motorola in 1997. Amazon's trailing free cash flow collapsed 95 per cent year-on-year, as a single quarter of capital spending nearly matched its full annual operating cash generation. Across Amazon, Alphabet, Meta and Microsoft, combined CapEx ran to $131 billion for the quarter, close to their combined underlying net income from operations once one-off mark-to-market gains are stripped out.

This is capital intensity with no real precedent in modern corporate history. It is also not the AI economy you held in 2024.

The 2024 AI trade was a single bet. Long the whole stack, financed out of free cash flow, with revenue arriving in real time. The 2026 AI economy is four businesses, each with its own capital structure, its own buyers, its own competitive logic. Three of them are largely outside venture's reach. The fourth is what we are paid to build.

The four layers

Layer one is the compute supply chain. ASML, TSMC, SK Hynix, Samsung, Micron, Nvidia, Broadcom, Marvell, Vertiv, Eaton, the data centre real estate platforms. The picks and shovels. Capital intensity is structural at this layer: a single advanced-node fab requires twenty-plus billion dollars of state-backed financing; an EUV lithography tool costs almost half a billion to deploy. New entrants need sovereign capital. The investment cycle here drove much of the global equity rerating across 2024 and 2025. The structural moats remain.

Layer two is the compute infrastructure. Amazon, Alphabet, Meta, Microsoft, and a small generation of neoclouds. The buyers of layer one. The 2024 case for this layer rested on a clean equation: real revenue, real moat, no leverage. The 2026 case rests on a different equation. Century bonds. FCF compression. Combined hyperscaler CapEx in a single quarter close to their combined quarterly underlying earnings. The revenue is genuine. The risk profile is not what it was eighteen months ago.

Layer three is frontier labs. OpenAI, Anthropic, Mistral, xAI, plus a small set of Chinese laboratories whose models now occupy four of the top five positions on the largest global open-source inference platforms. Anthropic's annualised revenue run rate moved from $9 billion at the end of 2025 to $19 billion by March 2026, and to roughly $30 billion by April, predominantly through Claude Code adoption. The capital required to compete at this layer has scaled past venture: the 2026 lab raises are sovereign-cheque events, not Series rounds. This is no longer a venture business. It is private growth equity at scale.

Layer four is everything that sits on top. Applications, embodiment, sovereign-aligned infrastructure, vertical AI for specific industries. This is where domain expertise beats model scale, where customer relationships are vertical and slow to displace, where geography matters because procurement matters, where the unit economics still favour small cheques. It is also where the application surface is much larger than at any prior tech wave. Every industrial process, every workflow that touches the physical world, every embodied system. This is the layer where the next decade of company formation happens. It is also venture's natural ground.

Why the layers have separated

The 2024 AI trade did not need this distinction. The whole stack moved together, financed out of operating cash flow, with revenue scaling on top of capability. The mechanism that has separated the layers is mostly about how each one is now funded and who its buyers are.

Layer one is now a public-equity story largely priced in. Layer two has shifted from a free-cash-flow story to a leverage story; the rerating from here will be tested against debt-funded CapEx and the unit economics of AI inference at the customer. Layer three has reached scale at which no venture fund can address it; the question is consumer monetisation, not capability. Layer four is the only layer where the founders, the customer pull, and the operating economics still converge at venture cheque size.

Most institutional portfolios already hold layers one to three through public market exposure. The complement they do not hold, and cannot easily access, is layer four.

The shape is not new

The mobile cycle of 2007 to 2017 ran in the same shape. TSMC, Qualcomm, Apple and Google captured the silicon and platform layers as public-market winners. The application layer fragmented and produced WhatsApp (sold to Meta in 2014, with consideration eventually rising to about $19 billion as the stock component appreciated), Instagram (Facebook, $1 billion in 2012), Uber, Airbnb, Snap. The cloud cycle of 2008 to 2020 followed the same pattern. AWS consolidated infrastructure. The application layer compounded into Slack ($27.7 billion to Salesforce in 2020), Zoom, Stripe, Salesforce itself.

In both cycles, the lower-layer concentration was the structural inevitability. The application layer was where venture compounded. AI is shaped the same way, with one wrinkle: the supply chain has consolidated further. There is one EUV maker globally. Three memory makers. Two leading-edge foundries. By contrast, the application surface is broader than mobile or cloud, because the substrate is everything in the physical economy as well as the digital one.

Where the Fund invests

The Fund invests at the fourth layer. With its final investment closed on 12 January 2026, the Fund's portfolio is locked at 25 active companies and two prior exits. Q1 2026 is the first quarter where the picture has been complete. The rest of this letter is the Q1 report on the Fund's portfolio.

The Fund in Q1 2026

Performance

Q1 2026 was a quarter of measured commercial progress at the consolidated level. Consolidated CARR closed Q1 at £18.22 million, up £1.39 million in the quarter. The dollar-adjusted figure was $24.0 million.

Fund Metrics

Q1 2026 closes strongly with the Fund's final investments now complete:

·   Net IRR: 19.2%

·   TVPI: 1.41X

·   DPI: 0.11x

The Fund's portfolio, as it now stands

The Fund's deployment is complete. Its final investment closed on 12 January 2026. The Fund's portfolio stands at 25 active companies, with two prior exits.

The shape of the Fund's portfolio reflects a long-running conviction: The Fund has always been drawn to software that operates close to the physical world. Manufacturing, logistics, construction, agriculture, supply chains, infrastructure. The conviction predates "Physical AI" as a label and runs back through earlier funds where the Fund backed Industry 4.0 software for the physical economy.

Two new Fund investments closed in Q1

The Fund made two new investments in the quarter. The second was the final commitment of the Fund.

·   All3. All3 builds robotics and AI for construction productivity automation, applying physical AI to a sector that has barely moved in fifty years. The Fund's conviction comes from the founders, who are exceptional both individually and as a unit, and from a hardware platform that is already working in the field. Construction robotics is likely to become a competitive space, and the scope of ambition the team has set for itself is daunting.

·   Cursive. Cursive is building a closed-loop optimisation layer for self-improving AI agents in production.

Spotlight: Hive

Of the Fund's portfolio in the field today, Hive is one of the clearest expression of where the Physical AI thesis is now playing out commercially. Hive's platform lets a single operator control a fleet of autonomous industrial vehicles (forklifts, diggers, construction machines) from a centralised station, dramatically improving both productivity and safety. It is layer-four physical AI applied to a massive, unglamorous market.

Forward outlook

The Fund is fully deployed. The performance arc is now a question of what the 25 active companies build, sell and become.

Several are positioning for next-stage rounds across the next twelve to eighteen months.

From here, the work is converting the positions on the page into the outcomes the Fund underwrote.