Program Outcome Report Sample

Counting the Invisible: Why AI Is the New Proof of Conservation

Problem: Wildlife Monitoring Is Slow, Manual and Prone to Errors

Wildlife monitoring has always been labour-intensive and imprecise. Conservationists and renewable energy operators rely on manual observations, camera traps or periodic surveys that miss out on critical data. In the wind energy sector alone, bird and bat collisions with turbines remain a major environmental concern, yet traditional methods capture only a fraction of incidents. 

Post-harvest surveys, migration tracking and biodiversity assessments are slow, expensive and subject to human error or incomplete coverage.

The stakes are very high. Regulators demand accurate impact assessments for permitting, while operators need real-time data to minimise harm and maintain social licence. Without reliable monitoring, conservation efforts stall, renewable projects face delays or opposition and entire species go untracked. In an era of rapid climate action and biodiversity loss, manual methods simply cannot keep pace.

How Spoor Reframes Conservation as Data — Credibility Proven by AI That Tracks Species at a Large Scale

Spoor is transforming wildlife monitoring from guesswork into precise and scalable data. The Norwegian startup uses advanced computer vision and AI to turn ordinary cameras into intelligent sensors that detect, track and classify birds (and other wildlife) in real time. This reframes conservation as data-driven infrastructure — proving credibility through continuous accurate insights that enable better decisions for both industry and nature.

In 2026, as renewable energy expands globally, Spoor has shown that the new proof of conservation is technology that sees the invisible.

Solution: AI-Powered Video Analytics for Bird Strikes, Biodiversity Monitoring and Environmental Compliance

Spoor’s platform integrates with any high-resolution camera system (fixed or mobile) and uses proprietary movement plus object-based machine learning models to:

1.Detect and classify birds (and bats) with up to 96% accuracy.

2.Track flight paths, behaviour and collision risks in real time.

3.Generate automated reports for regulatory compliance, permitting and environmental impact assessments.

4.Provide actionable insights for turbine curtailment, site planning and mitigation strategies.

5.The system runs on edge devices for low-latency alerts and scales from single turbines to entire wind farms. It also supports offshore and onshore projects, delivering continuous monitoring even in remote or harsh environments.

Proof of Credibility: Deployed in Wind Farms and Conservation Projects; Validated by NGOs and Regulators

Spoor’s technology is already field-proven:

•Deployed across multiple continents with more than 20 of the world’s largest energy companies, including Vattenfall, RWE and Fugro partnerships.

•Real-world results include zero avian deaths recorded in long-term monitoring at Vattenfall’s Aberdeen offshore wind farm (June 2023–December 2024 study).

•Validated by independent bodies such as the British Trust for Ornithology (BTO) and used in regulatory processes for permitting and ongoing compliance.

•€8 million funding round in late 2025 to scale globally, following strong demand from the wind industry.

•The platform has set new industry standards for AI-powered biodiversity monitoring, with public case studies from sites like Utsira and the TetraSpar floating wind turbine demonstrator.

Impact: Customers Gain Compliance and Sustainability; Investors See Scalable Conservation Technology

For wind farm operators and renewable developers:

•Faster permitting and compliance with environmental regulations.

•Reduced risk of collisions through data-driven mitigation (e.g., smart curtailment).

•Stronger sustainability credentials and community relations.

For conservation organisations and regulators:

•Accurate and continuous data that informs genuine biodiversity protection.

•Scalable monitoring that replaces labour-intensive manual surveys.

For investors:

•High-growth market at the intersection of renewable energy and environmental compliance.

•Defensible AI models trained on real-world wildlife data.

•Clear path to expansion beyond wind into broader conservation and infrastructure monitoring.

Conclusion: How Spoor Emerged as the Company Making Conservation Data-Driven

Wildlife monitoring no longer needs to be blind. Spoor is proving that AI can count the invisible — delivering the accurate real-time data that lets industry and nature coexist.

By turning cameras into intelligent sensors, Spoor is giving operators, regulators and conservationists the insights they need to protect species while advancing clean energy. The future of conservation is not more people watching screens. It is smarter systems that watch continuously. Spoor is building that future — one tracked flight at a time.