Municipality/ Örnsköldsvik

Ecovibes

Ecovibes develops AI-based bioacoustic technology for scalable ecosystem monitoring. By analyzing environmental audio with advanced deep learning models, we automatically identify species from their acoustic signatures and transform raw sound into actionable biodiversity insights. Our platform enables cost-efficient, non-invasive monitoring without the need for field experts, reducing reliance on manual surveys. It also serves as a centralized hub for bioacoustic data, enabling continuous analysis as new recordings are added, benchmarking against historical baselines, and full traceability of results over time. Founded by PhD researchers at SLU, Ecovibes builds on scientifically validated methods. Primary application areas include forestry, mining, wind energy, and infrastructure development.

WE OFFER

  • AI-powered species identification and biodiversity monitoring from environmental audio
  • Standardized, auditable reporting aligned with environmental regulations and compliance frameworks
  • Centralized data platform for continuous monitoring, historical benchmarking, and full traceability

WE ARE LOOKING FOR

  • Pilot partners in forestry, mining, or wind energy to validate bioacoustic monitoring workflows at scale
  • Collaboration with industry and public sector actors to co-develop standardized biodiversity data practices.

SELECTED REFERENCES

  • Bioacoustic species detection for three-toed woodpecker (Picoides tridactylus) and capercaillie (Tetrao urogallus) using field audio from Swedish boreal forests
  • Audio analysis projects conducted in collaboration with SLU, SCA, and Holmen

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