Requirements and constraints
Inventory equipment, data, network, compute, and maintenance conditions.
Allow or reject optional analytics. Rejecting does not affect the site; formal analytics is currently disabled.
Custom integration
Define deployable edge intelligence around equipment, data, and operating constraints
Standard products may not match field interfaces, compute, environmental, or maintenance constraints, causing technical validation and operating needs to become mixed together.
Defining the problem, data, and integration boundary first reduces uncertainty through focused validation and produces a practical module and next-step path.
Inventory equipment, data, network, compute, and maintenance conditions.
Assess existing or candidate models against target hardware.
Separate data input, inference, and output into testable interfaces.
Validate performance, reliability, and operating flow within an agreed context.
Define the problem and success conditions
Review data availability and governance needs
Assess models, compute, and execution environment
Build system and equipment interfaces
Record results and remaining constraints
Confirm the business and technical problem
Inventory data and existing systems
Build a focused technical validation
Plan integration and delivery from the results
Integrate Edge AI, vision, equipment data, and anomaly events to support field monitoring and process decisions.
View solutionCombine multi-source sensing, anomaly rules, and Edge analysis into continuous monitoring, event records, and alerts.
View solutionUse power, equipment state, schedules, and demand data to observe energy use, flag anomalies, and assess control.
View solutionDeploy image models to Edge devices and connect cameras, video, RTSP, events, and structured output.
View solutionVision models run on edge devices to validate camera input, inference, structured results, and event integration.
Products used: Edge Vision · Custom Edge AI · Asterism
View case detailsMultiple sensor inputs, schedules, decisions, safeguards, and control outputs form a traceable field workflow.
Products used: Asterism · Environment Control · Custom Edge AI
View case detailsEvaluate how one Edge AI platform can be ported and adapted across CPU, GPU, NPU, and AI-chip environments.
Products used: Asterism · Custom Edge AI · Edge Vision
View case detailsProduct fit depends on data, equipment, safety, and operational constraints. Start with a focused conversation about the intended environment.
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