Ltome-Katip 2: The world’s first Indigenous-labeled AI dataset for biodiversity. Ethical AI for climate resilience from Africa to Amazon.

Ltome-Katip is the world’s first initiative to develop Indigenous-labeled biodiversity datasets for AI training, co-led by Samburu (Kenya) and Shuar (Ecuador) communities. It combines bioacoustic sensors, camera traps, and local knowledge to detect ecosystem change and species presence in data-scarce, climate-vulnerable regions.

Now entering its second phase, Ltome-Katip 2 seeks funding to scale its ethical AI infrastructure — expanding datasets, deploying new sensors, training Indigenous data stewards, and integrating findings into early warning systems for conservation and food security.

Built with Indigenous leaders, scientists, and partners like RIT, Namunyak Conservancy, MUSAP, and the GEO Indigenous Alliance, this project sets a new global benchmark for AI grounded in epistemological equity and climate justice.

We are seeking $500,000–$1M in funding to:

• Expand sensor networks across the Amazon and African savannahs

• Label and scale the world's first Indigenous bioacoustic training sets

• Train Indigenous youth as AI dataset curators and analysts

• Co-develop AI tools for wildlife monitoring and agroecological forecasting

• Ensure long-term ethical use, storage, and governance of the data

Ltome-Katip redefines how climate tech is built and how space data is used, who owns the knowledge, and what ethical AI can become.