From Data Capture to AI at the Edge
Scale your industrial fleet management from a single point of control
Turn industrial data into dashboards and actionable decisions
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Managing a growing fleet of industrial equipment no longer has to be complex. With the Savvy Industrial Platform, you can deploy, monitor, maintain, and update hundreds of Edge devices and their applications automatically and remotely.
From data capture to orchestration, everything is connected, standardized, and ready to scale without friction.
Integrate all your industrial assets in a matter of minutes thanks to our pre-developed connectors.
Normalize your data once and use templates to replicate the process across the rest of your machines.
Automate key tasks such as filtering, preprocessing, or applying formulas, without manual intervention.
Access clean, structured, and reusable data throughout your organization: a single source of truth for decision-making.
ASSET MANAGEMENT
Mapper
Variable definition
Protocols
Preprocessing
Filtering
Formulas and virtual sensors
Interoperability
Cloud, datalake, etc
EDGE ORCHESTRATION(e.g., kubernetes)
EDGE MANAGEMENT
Edge(Docker container)
[ App cluster ]
Manage your data flow flexibly, without limitations.
Send data directly to the cloud (Savvy or third-party) or to other systems on the plant floor, such as servers or other connected devices. The simplest and fastest way to get started.
Capture data from your machines and direct it to the edge, the cloud, the fog, or any other plant system. Our system imposes no limits: you decide where to process and use your data.
Don't just read data: send information back to the machine. You can generate visual alerts for the operator on the CNC or PLC, or activate automatic actions such as stopping an operation, adjusting parameters, or launching safety routines. Make decisions at the edge and react in real-time.
Certain machines have a bridge that must be configured.
Machines generate data in many ways depending on their brand, model, device type (PLC, CNC, etc.), communication protocol, and signal structure. Normalizing data for use by a Docker container requires individually configuring each machine, adjusting IP addresses, protocols and specific parameters.With Savvy's asset management platform, this process is automated, simplifying collection of data from all your machines efficiently.
Most of our customers carefully choose and filter information extracted from their machines, such as variables, memory addresses, data sizes and tags. This greatly optimizes the job of a data analyst, as they receive only relevant data and keeps costs down when persisting only the necessary data on the Cloud.Without a management platform, this procedure must be manually carried out on each machine, which poses a considerable effort. With Savvy, the entire process is automated, saving on time and resources.
In many cases, it is convenient to create virtual sensors that output data, by application of formulas over signals collected from your machines. This is particularly useful when choosing whether to relay results of calculations over said signals to the Cloud, or to the Edge.With Savvy, this process is simplified, enabling you to obtain more precise and fast results, with less effort.
With our system, you can collect data from your machines and relay it to the Edge (closest to the machine), to the Cloud, to the Fog, or to other plant-level systems, without limitations.The whole process is automated, seamlessly enabling flows of data, and ensuring efficient management of your entire industrial infrastructure.