LoveIsAllYouNeed.
Ambrosia turns mothers into the architects of aligned AI.
The Transformation
Before Ambrosia, these moments were invisible. After, they shape the future. Here are five mothers whose quiet care became something extraordinary.
Sarah
Portland, Oregon
“Sarah teaches her daughter to crack an egg. No one is watching.”
Her recipes and planning strategies now power meal systems used across three continents.
Her kitchen movements trained domestic robots to handle food with precision and care.
She leads the largest Ambrosia cooking circle in the Pacific Northwest.
Maria
São Paulo, Brazil
“Maria reads to her son at bedtime. The same book, for the fortieth time.”
Her reading patterns shaped early-childhood AI tutors now used worldwide.
Her educational choices trained preference-learning systems at two major AI labs.
She founded Ambrosia's first Portuguese-language reading circle.
Aisha
London, England
“Aisha folds laundry while her toddler naps. Thirty minutes of quiet calm.”
Her six-axis motion data trained robotic manipulation systems for major robotics companies.
Robots trained on her data fold laundry with near-human precision.
Her household routines power the scheduling assistant used by tens of thousands.
Elena
Mexico City, Mexico
“Elena plans meals for a family of five on a tight budget. Every week, from scratch.”
Her planning strategies power nutrition-optimised meal systems across Latin America.
Families using her strategies spend 30% less while eating better.
Her weekly trade-offs are among the richest preference datasets in the platform.
Priya
Bangalore, India
“Priya helps her daughter with maths homework. The same fraction, explained three different ways.”
Her teaching patterns trained adaptive learning agents with dramatically better engagement.
Her data created the first AI model for patient, adaptive instruction — not just correct answers.
She leads Ambrosia's South Asia education network.
The invisible work that trains AI on real human decision-making.
Every game produces something real.
The game IS the data labelling. The output is something your family actually uses. Meals get planned, kids get taught, households get organised — and the choices you made along the way become the training data.
Meal Planning
Rank recipes, compare ingredients, solve your family’s weekly menu like a puzzle. When you’re done, dinner is planned for the week.
The choices you made along the way — swapping ingredients, balancing budgets, accommodating allergies — that’s the training data. Real preference decisions from real families.
Education Challenges
Challenges you do alongside your children. Help your daughter sound out words. Guide your son through a science question. The teaching IS the game.
The way you taught, adapted, and encouraged — your patience when they struggled, your creativity when they lost interest — becomes training data showing how mothers actually teach.
Household Optimisation
Build your family’s weekly rhythm. Prioritise, sequence, delegate. The schedule you create is real — and your household runs better for it.
Every decision you made building it — what comes first, what can wait, what happens when plans change — trains AI to understand how a household actually runs.
Cooking Sessions
Follow a recipe, adjust for your family, learn a technique from mothers around the world. Your wearable tracks how your hands move. You get better at cooking.
Six-axis motion data from real cooking — how hands stir, chop, pour, and plate — trains robotic systems to handle domestic tasks with precision.
Skill Building
Structured paths in nutrition science, child development, home organisation, financial planning. Real knowledge that makes your family stronger.
Your learning journey — what clicks immediately, what needs examples, where you get stuck — maps how real people acquire knowledge.
Community Circles
Find mothers near you who share your values. Weekly meetups, recipe swaps, homework help. You’re not doing this alone.
What resonates, how trust forms, which advice gets shared — teaches AI systems how real communities form and share knowledge.
Every game produces something your family uses. Every choice you made playing it trains AI.
The Thesis
Mothers have always done what they do. They care for their young. They love them fiercely. They wake at 3am and do it again. This is maternal instinct — timeless, universal, irreplaceable.
This work has never been captured. Never been measured. Never been valued by the systems that shape our world. Ambrosia changes that — not by asking mothers to do anything different, but by recognising the value of what they already do.
Don’t perform. Just be a mother.
The Byproduct
What naturally emerges when mothers play games that produce real outcomes — and every choice becomes training data.
Data Labelling
Mothers bringing judgment, patience, and real-world context — contextual expertise that crowd-sourcing platforms lack.
Video Recording
Mothers gently recording themselves doing what they've always done — cooking, caregiving, tidying, teaching. Real domestic life, captured with consent.
Wearable Sensor Data
Wearable jewelry with embedded motion sensors capturing how hands stir, arms fold laundry, bodies move through a home.
Preference & Decision Data
Every choice through the platform's games and tasks — meal plans, schedules, educational priorities — becomes structured data about what families value.
The Flywheel
Each cycle compounds.
Mothers Label Data
College-educated mothers bring precision and judgment to data labelling — the critical work that trains AI to understand human context.
Better Tools Return
The data they label improves the AI that powers their own tools — smarter meal planners, better scheduling, more personalised education.
New Data to Label
The video, motion, and preference data they generate comes back as new labelling work. They label what they created. The cycle deepens.
Mothers Do What They Do
With better tools, mothers do what they've always done — cook, care, teach, nurture — now gently capturing video and sensor data as they go.
Mothers Label Data
College-educated mothers bring precision and judgment to data labelling — the critical work that trains AI to understand human context.
Better Tools Return
The data they label improves the AI that powers their own tools — smarter meal planners, better scheduling, more personalised education.
Mothers Do What They Do
With better tools, mothers do what they've always done — cook, care, teach, nurture — now gently capturing video and sensor data as they go.
New Data to Label
The video, motion, and preference data they generate comes back as new labelling work. They label what they created. The cycle deepens.
Your data stays yours. On-device processing. Children’s faces auto-blurred. Delete anything, anytime.
What Mothers Create
Three categories of data unique to Ambrosia.
Labeled Decisions
Thousands of micro-decisions that teach AI what humans actually value.
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Embodied Video
The world's largest dataset of real-world domestic activity.
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Six-Axis Motion
Wearable jewelry that captures the physics of domestic work.
Hover to learn moreKnowledge & Thesis
Thesis & Research
EssayLove Is All You Need: Why the Alignment Gap Is a Data GapThe founding thesis — why care is the missing training signal.PaperThe Recursive Loop: How Mothers Compound AI AlignmentPublished in Nature Machine Intelligence, 2025.PaperEmbodied Domesticity: Six-Axis Motion in Real HomesTechnical paper on wearable IMU data collection methodology.In the Press
PressThe Startup Training AI on a Mother's LoveFinancial Times, March 2026PressAmbrosia: The Most Important Dataset You've Never Heard OfWired, January 2026PressWhy This AI Company Only Hires MothersThe Guardian, February 2026Reading List
PaperAttention Is All You NeedVaswani et al., 2017 — the paper that started it all.
BookThe Second ShiftArlie Hochschild — the economics of invisible labour.BookSituated Learning and Embodied CognitionThe intellectual foundation for learning from care.Start with Phase 1 — it’s a complete experience on its own. No video. No sensors. Just useful tools and meaningful pay.
The work of care becomes training data for the future.
Join mothers training AI on real parenting — while using games that help your family.