Across the climate innovation landscape, some of the most important questions remain unanswered simply because we haven’t been looking in the right places. Nobos is tackling that problem head-on by improving data representation in some of the most overlooked geographies on Earth.

With backgrounds in government data strategy and geospatial AI, the Nobos team realized that over 80% of biodiversity data is collected within one mile of a major road. That leaves vast ecosystems—especially in the Global South—largely invisible to climate models, humanitarian planners, and policy makers. These gaps distort our understanding of the planet and, even more importantly, delay action. Nobos exists to fix that.

Previous attempts to address these gaps have fallen short. Citizen science, while noble in intent, has proven insufficient in practice. Most citizen-contributed datasets lack consistency, quality controls, and scientific rigor. Data collected without training or standardized methods is rarely usable in high-stakes environmental modeling or policy contexts.

On the other end of the spectrum, deploying professional researchers into the field is cost-prohibitive, often inefficient, and typically yields small, isolated datasets. The Nobos solution overcome these limitations by building a repeatable, scalable model for high-quality environmental data collection.

Its solution is elegantly applied: build a scalable platform that empowers local communities to collect high-quality, AI-ready environmental data from remote and often ignored regions. Rather than sending highly specialized researchers into the field for one-off data gathering, Nobos partners with those already embedded in these ecosystems. It offers training, quality control protocols, and a modular platform to ensure the data is both credible and interoperable across use cases.

This model combines field logistics, scientific integrity, and scalable software, creating a new kind of infrastructure for applied environmental intelligence. Nobos supports both humanitarian and environmental goals, including coral reef health monitoring, flash flood early warning systems, and even forest fire risk modeling. More than gaining better data, its ultimate aim is better decision-making.

Crucially, Nobos doesn’t stop at data collection. Its approach incorporates AI-powered preprocessing and data structuring to transform raw environmental inputs into structured, analysis-ready datasets. From automated feature tagging to geo-referenced modeling inputs, the system ensures that each dataset meets the standards required by advanced machine learning tools used in climate research, disaster prediction, and environmental monitoring.

As co-founder Juan Camilo Mejía advocates, “So much of our environmental understanding is shaped by what’s easy to reach. But the truth lives in remote places—places without roads, without infrastructure, often without voice. If we want to build climate solutions that actually reflect on-the-ground realities, we need data from the places and communities that have been historically overlooked.”

Through RevHub’s CABI program, Nobos is refining its revenue approach—exploring everything from fee-for-service deployments to open data licensing and value-added analytics. It is also actively engaging with mission-aligned partners who need ground truth to validate their satellite models and meet emerging compliance and ESG requirements.

Ultimately, Nobos is a catalyst for applied innovation in climate intelligence, closing critical data gaps and amplifying the voice of the planet’s most underrepresented regions.

5 Ways Nobos Delivers Value:

• Closes data gaps in climate and humanitarian modeling, especially in the Global South 
• Offers a scalable platform that blends special ops logistics with data science rigor 
• Enables higher-quality, ground-truth datasets with transparency and usability baked in 
• Provides customizable outputs from raw data to enriched visualizations and model-ready formats 
• Serves as a trusted implementation partner for researchers, governments, and mission-driven companies