Ecosystem data can be noisy. Let’s hear the forest for the trees.
Echo Labs exists to make nature visible within human systems, to inform how we measure progress, allocate resources, and manage the balance between human activity and living systems.
The problem
We can't act on what we can't see
What can’t be measured can’t be managed, and what’s not represented gets overlooked.
Healthy ecosystems underpin our economies and societies. Because we lack the tools to measure them, they remain invisible in market and governance frameworks, leading to chronic underinvestment that threatens our way of life. Today, ecosystems are captured through infrequent, fragmented, and noisy data collection – a poor match for systems that are complex and dynamic. To close that gap, we need new ways to measure and represent them at scale. What does healthy Cornwall farmland sound like?
What We’re Building
Turning ecological noise into structured signal.
We are building a set of tools and methods that make ecosystems measurable and usable across science, policy, and industry. This means:
Multi-modal data
We integrate field observations, environmental and biological sensors, remote sensing data (across sources like LIDAR and satellite networks), and field-specific event-triggered sampling into a unified, dynamic, and shared resource intentionally built for (machine) learning.
Signal optimization
We blend data sources to amplify distinct signals of how ecosystems look, sound, and behave. This uncovers a common set of variables for optimized sampling and treats ecological data identically to geospatial data: a set of overlapping layers, each one capturing a dimension of the living world the others miss.
Representation
We define a structured representation of ecosystem state from the integrated and optimized data streams, enabling standardized tracking of condition over time. We test the utility, at each step, with partners across research, policy, and industry.
Our Vision
Towards ecological agency
Echo’s long-term goal is to make ecosystems continuously observable, modelable, and actionable, so their condition can shape decisions in governance, markets, and land use before collapse occurs.
A broader shift
Monitoring becomes prediction. Prediction enables adaptation. And more fundamentally, representation enables ecosystems to be meaningfully included in the frameworks that shape the world.
Who We Are
An interdisciplinary team
We came from machine learning, engineering, nature finance, data governance, and ecological research. Between us, we've built companies, research platforms across 25 countries, first AI models in ecology, led an X-Prize-finalist rainforest monitoring program, dispersed nature-finance investment, and created a digital ID for gorillas.
