We are approaching 10,000 users on Truleaf.org. Most have found us through the community side of Truleaf, where we share plant knowledge, growing guidance and free tools. If you have spent time here, thank you. We built these resources to be used, and it means a great deal to see more people finding them.
We also have news about the research work behind Truleaf. Kwáu, our AI engine for plant-science discovery, has been selected for the AltaLab Fall 2026 Cohort by AltaIR Capital.
These developments bring together two parts of our work: making plant science accessible to a wider community and building research tools that help people examine the evidence more closely.
What we want Truleaf to offer
A question about growing a plant can be specific. You may need to check its requirements, understand a nutrient calculation or find guidance for a particular stage of growth. Useful information should be easy to find and clear enough to apply.
That is the purpose of Truleaf's public resources. Our plant profiles, guides and tools give people a place to begin, with scientific sources available for further reading. Free access remains a defining principle of this work.
As the audience grows, we want to keep improving that experience. We care about whether a page answers the question that brought someone to it and whether the next useful step is easy to find.
Kwáu supports the research behind a decision
Kwáu is being developed for plant-science discovery and biological R&D. Its initial professional focus is crop protection, where research teams need to compare findings across organisms, crops, formulations and experimental conditions.
A team might want to understand what published evidence says about a biological intervention in a particular crop. The work involves finding relevant sources, deciding which studies belong in the review, extracting comparable information and checking where results disagree.
Kwáu organizes that work into repeatable research workflows. It keeps findings connected to their sources and preserves the context a scientist needs to assess them. Researchers set the question, inspect the evidence and judge what can support the next decision.
The intended users include scientists, R&D leaders and research organizations. We are developing the offer through focused pilots, beginning with one workflow and an agreed standard for a useful result. That gives a team something concrete to test against its current process.
Why we are joining AltaLab
AltaLab is a founder development and acceleration program created by AltaIR Capital and led by Igor Ryabenkiy. It combines practical work on a company's product, customers and business model with founder exchange and preparation for investment conversations. The Fall cohort's opening stage is a three-week online sprint. Fall 2026 program details.
We want to use the program to sharpen Kwáu's first offer. Which research problem should we focus on? Who needs it enough to make it part of their work? What evidence would show that a pilot is useful?
Those questions will shape how we develop the engine and explain it to research teams. The cohort gives us a setting in which to examine our assumptions and learn from other founders and the AltaLab team.
The work ahead
For Truleaf's community, our purpose remains practical: make reliable plant information and useful tools accessible. For Kwáu, the next step is to define a research workflow that a team can test, inspect and choose to use again.
We will share what we learn as the work develops, with clear context about what has been tested and what still needs work.
If you work in plant science or biological R&D, explore Kwáu and tell us about a research task that takes too long.