Presage Insights

Presage Insights, established in 2021 by co-founders Kamalpreet Singh Sidhu, Aman Bhambra, and Atul Sharma, operates in the predictive maintenance sector, targeting the global market projected to expand significantly by 2032. The Noida-based company provides a solution for industries aiming to reduce machinery downtime and optimize operational performance.

The firm's core offering is a comprehensive platform integrating Internet of Things (IoT) sensors with cloud-based software to facilitate real-time machine health monitoring. This system employs artificial intelligence-driven diagnostics to forecast and avert equipment failures. The technology is built to be sensor-agnostic, capable of connecting with various sensors through MQTT and Modbus protocols. The platform utilizes advanced signal processing techniques and multivariate time series models to analyze data across time, frequency, and time-frequency domains, enabling the detection of over 50 specific failure modes like imbalance, misalignment, and bearing faults. Clients receive real-time alerts and diagnostic reports, which are automatically generated and then validated by certified vibration experts to ensure accuracy.

The business model is centered on providing these predictive maintenance solutions to a diverse industrial client base, which includes sectors such as FMCG, steel, cement, automotive, and process manufacturing. The company serves notable clients like Adani, Abbott Healthcare, BPCL, and Kansai Nerolac. By digitizing maintenance operations, the platform helps clients shift from traditional reactive schedules to data-driven planning, which can lead to optimized spare parts procurement and extended asset life. Presage Insights has secured a total of $727K in funding over three seed rounds. The most recent round in February 2025, led by YourNest Venture Capital, raised $643K (Rs 5.6 crore). This capital is intended to expand market presence, scale operations, and further product development, with plans for international expansion into the Middle East, South America, and South Asia.

Keywords: predictive maintenance, machine health monitoring, asset management, IoT sensors, AI diagnostics, industrial IoT, condition monitoring, maintenance software, manufacturing technology, equipment failure prediction, vibration analysis, asset performance management, Industry 4.0, cloud-based software, downtime reduction, CMMS, industrial analytics, equipment reliability, rotating equipment monitoring, automated diagnostics