Room to explore, with the right boundaries
Good AI is like a good field: open enough to grow in, walled where it matters.
We design AI that is safe for children, private for organisations and efficient for the planet. Our boundaries are written down and published, so families, schools and businesses can see exactly where they are.
Our hero is a live simulation: a year in a wheat field, with a farmhouse, a dry-stone wall and a lone tree. Each season has its own life (a snowman in winter, a kite in spring, a rope swing in summer, a bonfire and hay bales in autumn) and each day brings its own weather: rain, fog, thunderstorms, gales or snow.
Our products
What is ClarityAILab?
ClarityAILab is a research-led AI company founded by PhD researchers. It builds two products: Clarity Kids, a multilingual AI learning companion for children aged 6 to 12, and Clarity Enterprise (MaiMai), which uses AI to remove the busywork from supply chain sourcing and purchasing. Every product follows the same three commitments: safe for children, private for organisations and efficient for the planet.
How is ClarityAILab different?
- Custodianship over ownership. We treat data as entrusted to us, not owned by us. Enterprise information and family moments stay under your control.
- Safety by design. Safeguards are built in, so our systems protect children and respect adults by default, without complex settings.
- Efficiency as a responsibility. We favour smaller, targeted models and route work to low-carbon cloud regions, so each interaction carries a lighter footprint.
- Governance in the open. Our policies are published in full and reviewed by an independent governance reviewer.
Why Efficiency is a Moral Choice
AI has a physical cost. We see radical efficiency as part of our ethical obligation to people and planet.
Data centres use water for cooling, electricity for processing, and generate CO₂ emissions. We design our systems to do more with less—using smaller, targeted models and a proprietary approach to reducing token usage, so each interaction carries a lighter footprint.
We avoid unnecessary model size, data movement, and retraining. Smarter design, less waste, the same high-quality experience. We also use innovative design and cutting-edge technology to reduce environmental impact without losing quality.
Research & Evidence
- Energy and Policy Considerations for Deep Learning in NLP (Strubell et al., 2019)
- Making AI Less “Thirsty”: The Environmental Footprint of AI (Li et al., 2023)
- MIT Tech Review: Training a single AI model can emit as much carbon as five cars
We use these tools with our own families and businesses. Download Corporate Charter (PDF)
Boundaries you can read
Every policy that governs our AI is published in full, from acceptable use to human oversight.
Insights
Our consulting company Building Resilience brings this work to supply chains, digital twins and decisions under uncertainty.
Building Resilience