Dianomic

Dianomic

Software Development

San Leandro, California 341 followers

Industrial Data Pipelines and Edge ML Insights and Actions for Bottom Line Results

About us

Dianomic is at the forefront of Industry 4.0 with its FogLAMP Suite, a cornerstone in Edge Machine Learning Operations (Edge MLOps). This technology is integral to the management of Operational Technology (OT) data pipelines, crucial for the deployment and operation of machine learning models at the edge. Surpassing traditional Distributed Control Systems (DCS) and SCADA systems, FogLAMP Suite orchestrates the entire lifecycle of edge machine learning, from project scoping and data acquisition to model training, deployment, and execution. Its ability to interface seamlessly with systems like the PI System and AVEVA Data Hub (ADH) facilitates real-time data analysis and the smooth integration of machine learning insights into OT operations. Furthermore, with components like FogLAMP Manage, the suite elevates data pipeline management with enterprise-scale configuration, monitoring, and role-based access control, supporting robust OT/IT integrations. By enabling advanced applications such as digital twins and predictive maintenance, Dianomic's FogLAMP Suite is a critical enabler of smarter, more efficient industrial operations.

Industry
Software Development
Company size
11-50 employees
Headquarters
San Leandro, California
Type
Privately Held
Founded
2017

Locations

Employees at Dianomic

Updates

  • View organization page for Dianomic, graphic

    341 followers

    Last day at #Distributech24 and feeling bittersweet! It's been incredible working alongside our partners, collaborating, and innovating together. (We’re also sad to go Kevin!)   Missed out on swinging by the booth to discover the wonders of the #AVEVA #FogLAMP Suite? Don't worry! Contact our passionate industry and tech enthusiasts Enrique Herrera, Bruce Becwar, Tom Arthur.   Modernizing your grid equipment is much easier than you think! 👍   #EnergyInnovation #Partnershipsmatter

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  • View organization page for Dianomic, graphic

    341 followers

    Distributed Compute is the key word. So many people / companies assume functionality for model development and deployment begins and ends in the cloud and the last mile to establish connectivity with the asset and actually DO SOMETHING is left to the customer to figure out. Live model execution and accuracy can only obtained with higher granular data with execution of the model next to the asset running on an Edge device; otherwise your a day late and dollar short of hitting the mark. FogLAMP by Dianomic provides that infrastructure to collect, analyze and execute models on a Edge devices next to the asset thus achieving True Distributed Compute. Another consideration - how do you manage 10's if not 1,000s of intelligent data pipelines all running one or more models at the edge? Short answer - you don't. You need a single pane of glass with useful status and template capability to scale and deploy at an enterprise level - take a look at what FogLAMP Manage provides. Dianomic can you help you on this journey.

    View profile for Enrique Herrera, graphic

    Director with global cross-functional industrial experience transforming manufacturing operations with digital technology solutions | Industry 4.0 | IIoT | Digital Twins | Cloud Computing | New product/plant launches

    Well, it seems like this pendulum swings again, from centralized to distributed. In reality, it is not either/or but rather both depending on the application. When latency or network reliability are primary consideration, then the #edge makes sense. When massive amounts of data and compute are required, then we have #cloud computing (which is a different kind of distributed computing). Managing the edge IT and data pipelines, make sense to be managed from the cloud. Having worked for a hyper-scaler and edge platform companies, I will give the consultant answer… it depends. Anyone have strong emotions for my friends in the industrial sector?

    Council Post: 2024 Predictions: Mass Migration From The Cloud To The Edge

    Council Post: 2024 Predictions: Mass Migration From The Cloud To The Edge

    forbes.com

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