Why 'owning the interface' is AI’s next frontier
The most meaningful value accrues where decisions are made. Let’s talk about the “interface” layer.
The AI stack is changing. After years of hype and attention on the infrastructure layer, models, data, and compute have become commoditised.
What we’re starting to see now is that the real leverage is moving to the interface layer (as in: how people are actually interacting with AI). This is where users make decisions and generate the feedback that improves the system. It is where value is created and, for startups and investors, where it can be captured.
In this piece, I’ll be looking at why this shift is happening and how AI-native interfaces are becoming the new strategic layer across industries like productivity, legal tech, logistics, and fund operations.
The shift toward interface-level innovation is already happening.
OpenAI recently acquired former Apple designer Jony Ive’s hardware studio io for $6.5 billion. The real signal wasn’t the deal size, but the focus: ambient AI designed to blend into everyday life without screens. We’re witnessing interaction move from something active and controlled to something embedded and passive.
Another signal for the changing interface of AI was the ElevenLabs hackathon, where a team built GibberLink, a protocol for AI agents to communicate using compressed audio. It’s early, but it points to a world where agents coordinate directly, without waiting for human input. How will agent-agent communication be structured, especially on platforms in which humans typically interacted — for example, over the phone? What happens when your personal booking agent calls your doctor's office's booking agent to arrange an appointment? How they interact is a big question.
The shift is changing how people build. Tools like CustomGPT and Google AutoML are making natural language the default interface for software creation. The rise of “vibe coding”, describing an outcome in plain terms and letting the system handle the structure, is lowering the barrier to entry. Gartner estimates that by 2025, 70 percent of enterprise apps will be built using no-code or low-code tools.
Each of these examples offers a view into how interaction with AI is evolving. Interfaces are no longer just access points. They define how we unlock the value of backend AI systems, where a good user interface allows the true potential of AI functionality to be unlocked. The first steps have been made and this shift is already influencing how tools are being designed, adopted, and embedded into daily work.
Innovation and the decision layer
As AI moves from experimentation into real-world use, interfaces have become the main point of leverage. We can see this play out across three layers: general-purpose assistants, embedded enterprise copilots, and domain-specific platforms.
Chat-based assistants like ChatGPT and Claude’s strength lies not just in language generation, but in how they turn complex inputs into simple, guided exchanges. But that was just the beginning. Chatbots reduce user autonomy and increase cognitive load. Why should we ask AI to do something when ambient computing can unlock AI pre-empting actions based on what you are already doing.
OpenAI’s move with Jony Ive shows they are thinking about what comes next: how people interact with AI will (and needs to) shift to AI-native devices and processes.
Enterprise copilots take this further by embedding themselves inside the tools where people already work. Microsoft 365 Copilot and Notion AI are not trying to replace existing applications. Instead, they surface suggestions and automate tasks within the same interfaces teams already use to write, calculate, meet and plan.In other words, everyone is realizing that the interface is the control point. While one might think that reality favors incumbents, this also creates a huge startup opportunity. The challenge is that giants like Microsoft are more easily able to embed AI into daily workflows, but startups that are able to “own the interface” in underserved workflows, such as procurement, logistics, construction, R&D, etc., will be positioned to become new category leaders in every domain.
Indeed, in more specialized environments, vertical platforms are emerging that target specific roles and decision points. Libra, a legal tech and Merantix Capital portfolio company, supports contract analysis, drafting, and research in one system. This year, the firm reached over €1 million in ARR thanks to an interface that understands legal language, firm-specific workflows and decision logic.
Canoe is doing something similar in fund operations. It automates data ingestion from custodians and portfolio systems, flags anomalies, and creates compliance-ready reports. The system integrates directly into operational workflows, which makes it easier to trust and easier to adopt.
Interfaces are becoming decision environments. When that happens, they start to accumulate operational data, model edge cases and adapt in ways that horizontal platforms cannot easily replicate.
Vertical Interfaces: Where AI Meets Real Work
Some of the most important changes are happening in domains that have historically been underserved by software, from fund administration to supply chain planning and everything in between.
These workflows tend to be complex, manual, and spread across systems that were never designed to work together. That has created an opening for AI-native platforms that lead with interface design. I’ll give a few examples from outside of our portfolio.
Procurement is one of the clearest cases. Mercanis has built a system that combines sourcing, supplier management, and contract workflows into one environment. The platform automates routine tasks like RFx processes and risk checks and continuously analyzes spend data to suggest savings opportunities. According to EU Startups, the firm raised €17.3 million in June, and reported that some customers experienced a 40 percent process cost savings and a 2.5 times improvement in efficiency.
In supply chain operations, Pelico helps manufacturers and logistics teams detect bottlenecks, manage disruptions and coordinate responses across departments. The system integrates live data from enterprise resource planning (ERP) and factory systems, as well as proposing real-time adjustments. For companies like Airbus and Safran, this has led to a 40 percent reduction in missing parts and a 15 percent lift in on-time delivery. By giving teams a shared interface to make decisions and act quickly, the platform improves both visibility and execution.
Raft is doing something similar in freight forwarding. The platform replaces manual processes with an integrated workflow that handles shipment tracking, invoice reconciliation and customs documentation. A customer-facing portal provides visibility into bookings, emissions data and quotes. The firm recently raised $30 million in Series B funding and has gone on to become a daily workspace for logistics teams.
What these platforms have in common is not a particular technical breakthrough, but a focus on owning the interface where decisions happen.
By embedding themselves in the day-to-day work of operational teams, they gather data that improves the product, reinforce habits that are hard to unlearn, and position themselves as the primary system of record. In environments that are structured but nuanced, where decisions happen continuously, interface ownership will continue to be a durable strategic advantage.
Our thesis: Interface ownership will create new category leaders
Across every example, one idea keeps showing up: the most meaningful value accrues where decisions are made. Interfaces that support that moment, where information turns into action, end up shaping behavior.
That’s why AI-native UX consistently outperforms tools that simply layer models onto old workflows. Retrofitting intelligence into legacy software often misses the timing, the structure, or the real context of the task. In contrast, deeply integrated vertical copilots are proving more resilient by becoming part of the decision process. We believe that the next generation of category leaders will be built at this layer.
If you’re building interfaces that change how work happens, we want to hear from you.
I also like to differentiate between system of records and system of action and intelligence. The legacy systems in business are the systems of action, we know need systems of action and intelligence, which help the users to take decisions faster, better more reliant.