AI & ML interests
Architecting the Gaia AI Engine. Our core research focuses on: Fine-tuning Large Language Models (LLMs) for environmental auditing, designing deterministic and stochastic multi-agent workflows (LangChain/LangGraph) for ecosystem telemetry, and deploying AI models to scale climate resilience and natural asset tokenization
Recent Activity
š³ Treebank AI
Tokenizing Natural Assets. Scaling Climate Resilience.
At Treebank AI, we unite the scientific rigor of environmental engineering with advanced machine learning infrastructure. We are building the technological standard for the new climate economy by transforming real-world ecosystem data into verifiable, transparent, and scalable financial assets.
š§ The Gaia AI Engine
Our proprietary intelligence layer, the Gaia AI Engine, is designed to tackle complex challenges at the intersection of natural capital and decentralized architectures.
Our core research and open-source contributions focus on:
- Domain-Specific LLMs: Fine-tuning and evaluating Large Language Models for sustainability contexts, environmental auditing, and complex telemetry interpretation.
- Multi-Agent Systems: Deploying deterministic and stochastic agentic workflows (via LangChain/LangGraph) to automate ecosystem analysis.
- Climate Datasets: Structuring and sharing high-quality, actionable data for environmental machine learning.
š¤ Join the Mission
We believe in the power of the open-source community to accelerate AI for the planet. Explore our models, benchmarks, and datasets, or connect with us to collaborate on the future of natural asset tokenization.
š Visit our platform