Imagine
Question the company before automating it. If intelligence had always been abundant, would you have built it this way? We find the work worth redesigning, and the work worth stopping.
Imagine what should exist. Engineer it into reality. Own what matters.
We help companies bring AI to their workforce, by redesigning work around intelligence rather than bolting AI onto yesterday's processes.
AI is crossing the line from software to labour.
But your organisation was never designed for digital labour. It was built around two assumptions: machines couldn't understand, and intelligence was expensive. Both are disappearing.
Don't use tomorrow's intelligence to automate yesterday's company.
The most valuable AI use case may be the process you never run again.
Don't rent what makes you different.
The VOLT 2037 thesis
What if the transformation we expect over decades happens in one? Five horizons, one decade. 2037 isn't the point. 2027 is.
2024–2026We are here
Agentic transition
AI moves from answering to reasoning, acting and performing work.
2027–2029
AI-native enterprise
The question shifts from where to deploy AI to how to redesign the company around it.
2029–2031
Intelligence gets a body
AI moves into robots, factories, vehicles and the physical world.
2031–2034
The convergence era
AI, robotics, biology, energy and materials accelerate one another.
2034–2037
The meaning economy
Judgement, taste, trust and meaning become the scarce resources.
How we work
Engineer
Strategy without building is theatre. We build working systems with your teams, so the future arrives as something you can touch, not a PowerPoint.
Own
Use the world's intelligence, but own what makes it yours. Your agents, data and models run on infrastructure you control, down to the silicon.
Where we build
About three quarters of the value from generative AI concentrates in four business areas.*
Customer operations
AI agents that answer, route and resolve customer requests across email, chat and phone. They connect to your own systems and hand over to your people when needed, without customer data leaving your control.
Marketing and sales
Assistants that research accounts, draft proposals and tailor outreach using your own CRM and product data, so sales teams spend their time with customers instead of on preparation.
Software engineering
Coding agents and internal developer tools connected to your repositories, tickets and pipelines. They run on models you control, so your source code stays inside your environment.
Research and development
Search and analysis across your internal documents, lab data and literature, so researchers find, compare and test ideas faster while intellectual property stays in-house.
*McKinsey, The economic potential of generative AI. Estimates, not forecasts.
The constraints are disappearing. What should exist next?
Tell us where you want to start. We'll come back with a first conversation, not a sales deck.