Writing observations is one of the most time-consuming tasks in early years settings. Practitioners know what they've seen—the challenge is finding time to write it up properly while still being present with children.
The observation writing problem
A typical observation workflow looks like this:
- Notice something worth recording
- Make a mental note (or a sticky note)
- Later, try to remember exactly what happened
- Write it up in formal language
- Link it to EYFS areas
- Format it properly
- Hope you've captured what made it special
By step four, the moment has lost its freshness. And how many observations never get written because the process takes too long?
AI writing assistance
Early Tree includes optional AI writing assistance. Here's how it works:
You provide the essence: Jot down quick notes, keywords, or phrases. "Aria building tower, knocked down, tried again, five blocks high, smiled when finished."
AI suggests expanded text: The system generates a properly formatted observation based on your notes, using language appropriate for EYFS documentation.
You review and edit: The AI suggestion is just that—a suggestion. You can accept it, modify it, or write your own. Your professional judgement always has the final say.
EYFS areas are suggested: Based on the content, the system suggests which learning areas apply. Again, you confirm or change these.
What AI doesn't do
The AI never invents observations. It can only work with what you tell it. It doesn't assess children, make developmental judgements, or replace your expertise. It's a writing assistant, not a practitioner.
Why this matters
Time saved on admin is time that can be spent with children. If AI can turn your quick notes into proper documentation in seconds rather than minutes, that's more time for meaningful interactions.
Our beta partners report writing observations faster and more frequently, with less end-of-day catch-up time.
Privacy and control
AI features are optional and can be disabled entirely. All processing respects data protection requirements—child data stays protected and isn't used to train external models.
Join the beta and experience observations that write themselves.