XpiderWEB AI: Predictive Maintenance AI for Industry

Industry leading multi-model AI for predicting machine failures months in advance

Glowing orange square with a black diamond shape in the center over a background of faint binary code.
Key Metrics

Industry-leading prediction

3mths

Predict failures up to 3 months in advance

Highly effective data

8m+ Hrs

Trained on 8,000,000 hours of real-world data

AI-Driven Insights

Xpiderweb

Unified Multi-Sensor Intelligence

XpiderWeb integrates ultrasonic, vibration, temperature, and electrical data streams into a single, coherent intelligence layer. By analysing these signals together instead of in isolation, it uncovers relationships and mechanical behaviours that traditional monitoring systems miss. This unified approach gives engineers a deeper, more accurate picture of machine conditions in real time.

Edge-Driven Processing

Rather than relying solely on cloud systems, XpiderWeb processes data at the edge. It filters noise, extracts features, and classifies mechanical behaviour locally, reducing bandwidth consumption and delivering faster insights. This edge-first approach is especially valuable in high-interference industrial environments, where clean signals and low-latency responses are crucial.

Private, Secure Architecture

XpiderWeb is engineered for environments where data ownership and privacy matter. All machine data stays within a secure, controlled ecosystem, with no dependence on external platforms. Clients retain full control over their operational information, ensuring compliance, confidentiality, and long-term autonomy over their industrial analytics infrastructure.

Scalable Industrial Deployment

Designed for factories of any size, XpiderWeb scales easily across floors, buildings, and multi-site operations. Its distributed architecture supports large sensor networks without performance loss, allowing companies to monitor hundreds or thousands of machines through one unified system. As needs grow, the platform expands effortlessly alongside them.

Key Features
Heatmap highlighting the words 'Pumps' and 'Servo Motor' among other technical terms like 'Chillers', 'Air Handling', and 'Centrifugal Pump'.
Diagram illustrating a central star-shaped icon connected by dotted lines to labels reading Ultrasonic Data, Thermal Data, and Vibrational Data on a black background.
Concentric rounded square outlines in gradient red and orange, with a stylized diamond shape inside a square at the center on black background.
Wave-like pattern of orange diamond shapes forming a zigzag line on a black background with faint gray dots.
AI analysis alert at 11:47am indicating motor bearing requires lubrication as part of future failure prediction.

Made for large teams and multiple locations

A graphic visually representing the Xpiderweb AI identifying issues

Ready to transform your asset reliability?