In this episode of the Colaberry AI Podcast, we explore how Tata Power CoE, in collaboration with Oneture Technologies, built a scalable AI-powered inspection system to modernize solar panel installations across India—leveraging the full power of Amazon Web Services (AWS).
As India accelerates its renewable energy goals, manual solar inspections became a major bottleneck: time-intensive, error-prone, and impossible to scale at the pace required. To solve this, Tata Power adopted a cloud-native AI approach that automates inspection, validation, and quality checks across large volumes of solar installations.
The solution uses Amazon SageMaker AI for model training and inference, Amazon Bedrock for image quality pre-checks and contextual guidance, and Amazon Rekognition for tasks such as Optical Character Recognition (OCR). Together, these services enable accurate, consistent, and real-time inspection workflows—dramatically improving operational efficiency.
The results were substantial: over 80% reduction in re-inspection rates, AI/ML accuracy exceeding 90%, faster installations, and significantly improved customer satisfaction. This episode highlights how applied AI, when aligned with real operational challenges, can become a powerful catalyst for sustainable infrastructure at scale.
🎯 Key Takeaways:
⚡ AI replaces slow, manual solar panel inspections with scalable automation
🤝 AWS services power end-to-end inspection workflows
🔄 Over 80% reduction in re-inspections and >90% model accuracy
📜 Amazon Bedrock enhances image validation and contextual decision-making
🌍 AI accelerates renewable energy adoption and operational excellence
🧾 Ref:
How Tata Power CoE Built a Scalable AI-Powered Solar Panel Inspection Solution – AWS Blog
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