About
Conservation Metrics (CMI) is a science-driven organization that co-creates biodiversity and biocultural monitoring systems tailored to the needs of conservation practitioners, Indigenous communities, and environmental organizations. Rather than offering a one-size-fits-all platform, CMI works as a collaborative partner to build rigorous, scalable, and cost-effective monitoring programs from the ground up. At the core of their approach is the integration of passive acoustic monitoring and camera trap technology, which automates wildlife detection that traditionally required intensive manual fieldwork. These technologies are paired with cutting-edge remote sensing, machine learning pipelines, and robust statistical frameworks to generate reliable biodiversity metrics at large scales. CMI also specializes in supporting Indigenous guardianship programs, providing monitoring tools rooted in the self-determined goals and worldviews of Indigenous communities — recognizing their role as stewards of biodiversity hotspots. On the data infrastructure side, CMI guides clients through the full data lifecycle: tool selection, data management, ML model deployment, and the delivery of decision-ready insights. With a global footprint spanning 24 countries, 72 partners, and nearly 15 million hectares monitored, CMI is trusted by NGOs, governments, research institutions, and Indigenous organizations seeking to move beyond ad hoc surveys toward sustainable, long-term ecological monitoring. Their work is ideal for entities that need scientific rigor, technological integration, and community-centered approaches to conservation data.
Key Features
- Passive Acoustic Monitoring: Automated detection and analysis of wildlife sounds using acoustic sensors, reducing the need for labor-intensive manual surveys.
- Camera Trap Analysis: AI-assisted processing of camera trap imagery to identify and track wildlife species at scale across large landscapes.
- Indigenous Guardianship Tools: Monitoring frameworks co-designed with Indigenous communities to support self-determined land stewardship and cultural preservation goals.
- End-to-End Data Infrastructure: Comprehensive support across the full data lifecycle — from tool selection and data management to machine learning integration and insight delivery.
- Remote Sensing & Statistical Analysis: Integration of satellite remote sensing and rigorous statistical methods to produce reliable, large-scale biodiversity metrics.
Use Cases
- Large-scale wildlife population monitoring across protected areas and Indigenous territories using acoustic sensors and camera traps.
- Supporting Indigenous land guardianship programs with custom monitoring frameworks that reflect community-defined conservation priorities.
- Biodiversity baseline assessments for conservation planning, impact evaluations, or carbon and biodiversity credit verification.
- Building data infrastructure for environmental NGOs and government agencies to manage, analyze, and report on long-term ecological datasets.
- Acoustic species detection and identification for endangered or cryptic wildlife in remote or hard-to-access ecosystems.
Pros
- Massive Scale Monitoring: Capable of monitoring tens of millions of hectares across dozens of countries, making it suitable for large-scale conservation programs.
- Community-Centered Design: Programs are co-created with local and Indigenous partners, ensuring cultural relevance and long-term sustainability.
- Automated & Cost-Efficient: Machine learning and automated sensors dramatically reduce the cost and labor traditionally associated with wildlife surveys.
- Scientific Rigor: Statistical frameworks and peer-reviewed methods underpin all monitoring programs, ensuring data reliability for research and reporting.
Cons
- Professional Services Model: CMI operates as a consulting and co-creation partner rather than a self-service platform, which may require significant engagement time and budget.
- Niche Focus: Primarily suited for conservation, environmental, and Indigenous organizations — not broadly applicable to general data analytics use cases.
- Limited DIY Options: Organizations seeking off-the-shelf software tools may find CMI's collaborative, custom-built approach less accessible without dedicated project teams.
Frequently Asked Questions
What types of organizations does Conservation Metrics work with?
CMI works with a wide range of partners including NGOs, government agencies, research institutions, and Indigenous communities — anyone involved in biodiversity monitoring, land stewardship, or ecological research.
What technologies does CMI use for wildlife monitoring?
CMI leverages passive acoustic monitoring devices, camera traps, satellite remote sensing, machine learning models, and statistical analysis frameworks to detect and track wildlife at scale.
How does CMI support Indigenous communities?
CMI co-designs monitoring tools that align with Indigenous communities' self-determined goals and perspectives on land stewardship, ensuring programs are culturally grounded and community-owned.
How large a geographic area can CMI monitor?
CMI has monitored nearly 15 million hectares across 24 countries through over 6,900 survey locations, demonstrating the scalability of their monitoring infrastructure.
Does Conservation Metrics offer data management and analytics support?
Yes. CMI supports the entire data lifecycle, including tool selection, data pipeline setup, machine learning deployment, and the translation of raw data into actionable conservation insights.
