Proven on the
ground and on stage.
Recognized for innovation in conservation technology, and tested in real parks.
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International Conservation Technology Conference
ICTC · Peru 2026
We were invited to demonstrate our work in two sessions:
- Unlocking Innovation From the Ground Up: grassroots funding pathways in conservation technology, under WILDLABS.
- Running Conservation Technology Efficiently: running models from edge to cloud on Arm architecture.
We demonstrated hardware including RPi5, Grove Vision AI v2 and STM32 N6, showing real-time model performance on the edge and their varying power efficiencies for field deployment.
Deep Learning Indaba Ideathon
Bias: endangering species and model performance
Camera traps across Africa generate millions of images, but up to 75% are false triggers, and the species most critical to conservation are the ones current AI models fail to detect. Tools like SpeciesNet perform well on common animals yet miss the majority of leopards, pangolins and other vulnerable species.
Our project integrates IUCN threat metadata, strengthens representations of rare species through taxonomic and few-shot fine-tuning, and builds uncertainty-aware models that flag doubtful cases for ranger review.
Camera traps in Nairobi National Park
Field testing & impact
In this milestone deployment we installed and calibrated a customized grid of camera traps across key sectors of Nairobi National Park.
The deployment stress-tested our edge models in diverse field conditions, giving us hard data on power management and data transmission, and contributing to local wildlife monitoring.
Evi4Dev 2025
Elevate AI Challenge winners
Following our win at the Elevate AI Challenge 2024, the team was invited to showcase our camera trap innovation at Evi4Dev 2025.
The event let us demonstrate our edge-to-cloud wildlife monitoring ecosystem to global development leaders, and show how integrated hardware and software set new standards for biodiversity tracking and anti-poaching across Africa.
