Your AI. Your workflows. Your judgement.
We build digital apprentices and the preference data that improves them: private to your organisation, grounded in how your experts actually work.
An apprentice doesn’t arrive fully autonomous. It grows into your workflow instead of replacing your judgment. As it earns trust on execution, you get time back for exploration, engagement, and the work only you can do.
Human direction matters because most AI adoption puts automation first. We aim to invert that path: people and judgment at the top, AI earning a narrower scope of execution beneath them.
We’re in active development with design partners who want private AI that learns their expertise.
Current work
Experts reveal knowledge in practice that they cannot fully articulate in instruction. We study how apprentices infer methodology, judgment, and style from observation — capturing the why, not just the what.
Rather than treating each AI response as disposable, the apprentice explores alternatives, compares them against the expert's methodology, and captures learning signal from work that was already happening.
When different responses contain complementary strengths, Pheo studies how to combine them into a better answer while preserving grounding, provenance, and human review.
Quality is not one number. Pheo evaluates work across task-relevant dimensions such as correctness, style, safety, completeness, and methodology fit, then learns which dimensions matter for each domain.
Your team's corrections, approvals, and professional preferences become structured data with full provenance — owned by you. Usable to improve apprentices and private AI on your workflow.
Extending the apprentice paradigm beyond knowledge work to physical domains: surgical technique, athletic training, and robotics — where tacit knowledge is encoded in motion, not just language.
Team
Pheo is an applied data science company based in San Francisco and Abu Dhabi. We continue to work with professionals in healthcare, finance, legal, professional consulting, and coaching — anywhere expertise is hard-won and worth preserving. We’d love to hear from you.
Reach outVision
Pheo stands for people helping each other. We want to prove that the rise of AI and human flourishing are compatible if we approach the future thoughtfully.
Most of us spend our days on work that leaves too little room for what really matters. AI can change that if it is adopted deliberately with care. Work is becoming more focused on learning, teaching each other, and directing AI with the kind of judgment that only experience builds. With the right approach to AI adoption, people will have more time for deep thinking, for creative ambition, and for each other.
We want to live in a world that is more human and enabled by AI, so we created pheo.ai to make that happen for as many people as possible.
We use a framework called the 3 E's to guide every AI adoption we design: Execution, Exploration, and Engagement. All work can be thought of as a bundle of tasks, and the 3 E's classify those tasks by how AI should relate to them.
Scoped, well-defined, fully contextualised tasks that AI can handle with human oversight: scheduling, data processing, document formatting, information retrieval, and agentic workflows.
Searching, synthesising, and sensemaking where human judgment, preferences, and experience matter most — and AI expands what people can do.
Dialogue, trust-building, care, and creative collaboration that should remain authentically human. These tasks should never be replaced by AI, but can be scaled and supported by it.
Most technology stacks sit on a familiar shape: automation and platform efficiency at the top, humans fitted to the system at the bottom. Pheo inverts that — people and judgment at the apex, AI earning a narrower scope of execution beneath them.
Default stack
Automation-first adoption
Pheo
Human-first adoption