Case Study: PolyPerception achieves real-time waste sorting insights with TimescaleDB

Poly Perception develops AI-powered waste analysis solutions that optimize recycling and sorting processes through real-time monitoring and data-driven insights

PolyPerception, a Belgium-based AI startup, helps waste sorting facilities detect, classify, and estimate the weight of materials in real time to improve recycling efficiency and purity. As its system generated large volumes of time-series data, the company struggled with slow processing, limited data retention, and an inability to continuously analyze waste streams. To address these challenges, PolyPerception turned to TimescaleDB from Timescale.

Using TimescaleDB’s continuous aggregates and time-series storage capabilities, Timescale helped PolyPerception process data more efficiently and deliver real-time monitoring for waste sorting operations. The result was reduced latency, better data management, and more accurate, faster AI-driven classification, giving customers improved throughput, stronger sorting performance metrics, and more actionable real-time insights.

PolyPerception

Nicolas Braem

Co-Founder