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Biometrio

This company provides nature analytics through a dashboard integrating geospatial, remote sensing, and in-situ acoustic monitoring data. They utilize deep learning models to process diverse data sources for biodiversity and land use assessments. The platform delivers precise, transparent metrics tailored to specific project areas and measurement objectives.

Saarbrücken, GermanyFounded 2022373K+ followers
Updated 4 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Product

Problem

Traditional biodiversity assessments are often time-consuming, labor-intensive, and lack the granularity required for effective land-use management and conservation efforts. Integrating diverse data streams like satellite imagery, acoustic recordings, and camera trap data into a cohesive analysis presents significant technical challenges.

Solution

Biometrio provides an AI-powered nature analytics platform that unifies geospatial, biodiversity, and in-situ sensor data to deliver comprehensive ecological insights. The platform leverages advanced satellite analytics for high-resolution geodata processing, creating locally adapted maps and metrics. It also incorporates species identification from acoustic monitoring and wildlife camera data, enabling non-intrusive and cost-effective species presence and abundance assessments. This holistic approach, powered by deep learning models, offers radical transparency and accuracy in biodiversity assessments, with a customizable dashboard for diverse project needs.

Target Audience

Biometrio serves environmental consultants, conservation organizations, land developers, and government agencies requiring detailed and scalable biodiversity monitoring and land-use impact assessments.

Features

  • Integrates global geospatial and biodiversity datasets with in-situ sensor data (acoustic and camera trap) for holistic ecological analysis.
  • Utilizes advanced satellite analytics to process high-resolution geodata into project-specific maps and metrics.
  • Employs deep learning models for species identification from acoustic recordings, capturing wildlife vocalizations and environmental sounds.
  • Features a Nature Analytics Dashboard for transparent visualization of biodiversity and land-use insights, including uncertainty quantification.
  • Offers customizable analytics solutions tailored to specific project areas, geographical scales, and temporal objectives.
  • Supports integration of third-party or existing project data to enhance analytical depth.
  • Provides rapid insights into biodiversity and land use through efficient data processing pipelines.
This profile is AI-generated and may contain inaccuracies.