Partner Success with AWS / General Public Services / Rwanda
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Wildlife-Centered AI: How AWS and Tehanu Use Generative AI to Give Wildlife a Voice in Global Conservation
Discover how Tehanu uses groundbreaking AI solutions to empower interspecies economies, advancing conservation and global biodiversity efforts.
$1.55B
estimated financial value of Rwandan mountain gorillas
93%
accuracy in gorilla face recognition using ranger observations, camera traps, and crowdsourced imagery
110x
faster analyzing data than human experts
Overview
The Tehanu project in Rwanda’s Volcanoes National Park has demonstrated groundbreaking use of generative AI to infer and act on the interests of mountain gorillas. Leveraging technology solutions from Amazon Web Services (AWS), AWS Partner Anthropic, and with the support of AWS Partner Adastra, Tehanu created an automated pipeline to process behavioral data of gorillas, enabling the first-ever digital financial transactions by a non-human species. The AI solution synthesized vast academic and observational data, aligning conservation actions with species-specific preferences while supporting biodiversity efforts. This scalable, innovative approach sets a precedent for using AI to foster coexistence across species worldwide.
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From Research to Action: Advocating for Non-human Species in the Global Economy
While Homo Sapiens (commonly known as the human race) share our planet Earth with 8 million non-human species, our attention and conservation efforts reach only a small percentage of this vast biodiversity. Many remain unstudied, with only 2 million documented by science, leaving the majority unacknowledged or forgotten. Animals, trees, and other species play vital roles in sustaining the global economy, which cannot thrive if resources benefit only humans. Tehanu believes that these species must actively participate in our global economic framework to ensure their survival and the planet’s prosperity.
In 2024, Tehanu sought to launch a project focusing on a family of mountain gorillas in Rwanda’s Volcanoes National Park, on the border with Uganda and the Democratic Republic of Congo. While mountain gorillas represent a rare success story in conservation, many efforts to protect other species suffer from fragmented research, limiting the ability to generate implementable findings. With the objective to automate the aggregation of academic studies, such as the gorillas’ behavioral preferences, Tehanu hoped to enable informed policymaking that would support biodiversity. This innovative approach aimed to improve intervention accuracy—such as suggested interests on anti-poaching measures and veterinary care—for mountain gorillas while reducing negative impacts on other species within their ecosystem.
Using generative AI to process and extract patterns from a comprehensive behavioral dataset on the mountain gorillas, the project set out to demonstrate how AI can uncover the nuanced needs and preferences of non-human species, translating them into actionable insights for human-centered economic systems. By integrating the interests of non-human species into market dynamics, Tehanu aims to create a sustainable model that fosters coexistence and mutual benefit between humans and the broader natural world.
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Together with AWS we have made the first step in a multigenerational journey where AI can help us better understand the interests of other species—not just humans—and build new systems that work in their interests.”
Jonathan Ledgard
Co-founder and CEO, Tehanu
Scalable AI Solutions on AWS Support a New Era of Wildlife Conservation
The project’s success relied heavily on the scalability and efficiency of the AWS Global Infrastructure, which formed the backbone of a solution capable of processing extensive unstructured data. The team partnered with conservation experts to refine its system, ensuring the complex needs of mountain gorillas were comprehensively captured. Adastra helped synthesize data from hundreds of academic papers, and analyzed them using a structured pipeline developed by using Amazon Bedrock—the easiest way to build and scale generative AI applications with foundation models. This pipeline utilized Large Language Models (LLMs) to extract, validate, and categorize gorilla preferences. Adastra’s meticulous process of iterative refinement, expert review, and clustering ensured both the accuracy and transparency of insights. The team also conducted human-led inference experiments using an interview guide, followed by thematic analysis, to code the responses and derive key themes— finding that AI-generated preferences offered more operational recommendations than those generated manually.
Adastra implemented AWS services, including Amazon Bedrock, Amazon Simple Storage Service (Amzon S3), and AWS Lambda to support the seamless storage and serverless execution of generative AI features. Using Anthropic’s Claude 3.5 Sonnet model in Amazon Bedrock, Tehanu accurately identified gorilla preferences at a level comparable to human experts, but with significantly greater efficiency. This breakthrough in operational efficiency enables conservationists to analyze and respond to wildlife needs more comprehensively, accelerating conservation efforts that traditionally required extensive manual analysis and expert consultation. AWS also offered scalable compute resources, including Amazon S3, Amazon Bedrock, Amazon Lambda, and Amazon CloudWatch. These resources enabled Tehanu to manage databases for the Internet of Species, infer species interests, and maintain application programming interfaces (APIs) for digital monitoring, reporting, and verification (MRV).
Pioneering Species-Centric AI for Wildlife Preservation
Leveraging Adastra’s AI expertise and the comprehensive cloud capabilities of AWS, the project revealed new ways technology can enhance our understanding of Earth’s biodiversity and support climate change mitigation efforts. Using Anthropic’s Claude LLMs, the model provided insights as accurate as human experts, but with far greater detail and actionable recommendations. Notably, the project pioneered AI-inferred interests for species, an unprecedented achievement in conservation science.
Amazon Bedrock enabled sophisticated experimentation with large language models, providing the foundation for Tehanu to develop a scalable approach to analyzing and understanding species behavior and needs. The initiative focused on inferring the preferences of Rwandan mountain gorillas by analyzing scientific literature and expert interviews, resulting in one of the most detailed valuations of a wild animal population. Covering 440 mountain gorillas, Anthropic’s Claude integrated diverse datasets—including census reports, genetics, health, diet, social behavior, and movements. This unique approach advanced data mining, developed an API for preference identification, and established a foundation for broader applications.
Through a collaboration with Gorilla Vision—an AI research project in Berlin, Germany designed to analyze the behavior of gorillas and identify better ways to protect them—the project achieved over 93% accuracy in gorilla face recognition using ranger observations, camera traps, and crowd-sourced imagery. The project also created an AI-assisted model to generate and validate species-specific interest data, integrated into a secure blockchain system. This system enabled verified conservation actions to trigger payments via Rwanda’s MTN MoMo mobile money network. Remarkably, this allowed gorillas to hold a digital identity, express preferences, and even spend money—marking a historic first for non-human species. The estimated financial value of Rwandan mountain gorillas now stands at $1.55 billion, equivalent to nearly 10% of Rwanda’s annual Gross Domestic Product (GDP).
As a comparison, AI-inferred gorilla preferences from interview transcripts with park rangers were generated in just 13 minutes, compared to 24 hours required by four human experts. With comparable results, generative AI was 110 times faster, highlighting its efficiency in analyzing data and comparing methods. This innovative approach has established a benchmark for using AI in biodiveristy conservation, providing a replicable and impactful model for future efforts involving other species worldwide.
About Tehanu
Tehanu is building the infrastructure that facilitates a circular flow of money and data between humans and other non-human species, creating an economy that benefits all life forms. Through its groundbreaking concept of “Interspecies Money,” Tehanu facilitates the transfer of financial value across species by connecting biodiversity funders with human agents acting as custodians of nature. Leveraging generative AI and blockchain technology, the platform processes behavioral data to identify non-human species’ needs and translates these into actionable, pro-nature services within human-centered economies.
About AWS Partner Adastra
Adastra empowers organizations to unlock the full value of their data with accessible, resilient infrastructure and expert solutions in Artificial Intelligence, Data Analytics, Cloud, and Governance. With over 20 years of experience, Adastra helps businesses of all sizes transform operations, enabling smarter decisions and driving growth.
About AWS Partner Anthropic
Anthropic is an AI lab whose research and products put safety at the frontier. Anthropic is dedicated to ensuring the world safely makes the transition through transformative AI. Their multidisciplinary team creates reliable, interpretable, and steerable AI systems. Anthropic’s flagship product is Claude, a large language model that offers the best combination of speed and performance.
AWS Services Used
Amazon Bedrock
Amazon Bedrock is a fully managed service that provides a single API to access and utilize various high-performing foundation models (FMs) from leading AI companies. It offers a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI practices.
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Amazon S3
Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.
AWS Lambda
AWS Lambda is a compute service that runs your code in response to events and automatically manages the compute resources, making it the fastest way to turn an idea into a modern, production, serverless applications.
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