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Edge AI, IoT, and connected digital twins provider ClearBlade announced the launch of its new Forecasting AI Component, now available inside the company's flagship Intelligent Assets application. This enhancement empowers businesses to generate live, predictive models of asset performance using historical and real-time data without custom code or advanced technical expertise.
Forecasting AI allows users to anticipate future equipment states, resource needs, and operational risks by selecting asset attributes, applying machine learning models, and viewing predicted outcomes alongside current data.
This is the third in ClearBlade's growing AI Component library, joining the Anomaly Detection and Intelligent Video Analytics AI components. Each component works independently yet supports ClearBlade's strategy of delivering modular, edge-ready AI without forcing customers to rip and replace existing systems. With Forecasting, users can now select attributes to predict inside Intelligent Assets, generating future-state values based on historical telemetry, usage patterns, environmental signals, and other asset inputs.
What It Does
Predict future values for asset attributes using historical data, environmental factors, and usage patterns.
Run forecast models at the edge to predict performance even when connectivity is disrupted.
Compare real-time telemetry with predicted values inside dashboards and asset history views.
Use GenAI to suggest meaningful inputs for forecasting targets.
Explore upcoming operational periods using an updated time-range control.
Access all features through a no-code interface designed for operational and business users.
Forecast asset attributes in real time using AI models trained on historical data.
Create configurable predictions on asset attributes inside Intelligent Assets.
The Forecasting AI Component brings machine learning into everyday workflows. Users can configure forecasting inside Intelligent Assets by selecting attributes to model and viewing results directly within the operational context.
ClearBlade Edge provides a lightweight runtime built specifically for industrial environments where connectivity is intermittent, compute is constrained, and decisions cannot wait for a round-trip to the cloud. Forecasting AI leverages Edge to compute predictions directly where data originates and maintains continuous operation during network outages.
Real-World Applications
Predictive Maintenance: Anticipate equipment failures and schedule service before downtime.
Smart Energy: Forecast generation, storage, and load in solar and grid systems.
Facility Optimization: Predict HVAC demand and occupancy levels in smart buildings.
Fleet Monitoring: Forecast fuel levels, engine temperature, and component wear.
Utility Planning: Model future water flow and demand across networks.
Inventory and Supply Chain: Plan parts and replenishment based on real usage patterns.
AI-Powered, Enterprise-Grade Intelligence
ClearBlade used Google Cloud's Vertex AI and BigQuery platforms and Google’s Gemini models to build the Forecasting AI Component, which delivers enterprise-grade intelligence within ClearBlade's digital twin platform.
Find out more about the market for industrial edge compute platforms.