Find out how others have succeeded

PiSA, a Mexican pharmaceutical manufacturer operating 16 plants and 17 specialty production lines, recorded data machine by machine according to its own criteria, resulting in conflicting readings that made real-time decisions unreliable and required evidence for every batch to be reconciled manually. Working with the integrator EISOT, the company used Barbara's platform to normalize data from each line at the edge and consolidate it into a single authoritative repository within its own facilities, completing the first phase of its digital twin.

Cuerva ran a distribution network where concentrators, low- and medium-voltage supervisors, and MV remote units each operated on their own protocol at different voltage levels, making congestion and overvoltage in the low-voltage grid detectable only after the fact. Using Barbara's platform, the company consolidated a secondary substation onto a single node and ran Gridfy's AI forecasting models directly within it, giving operators a six-hour forward view of the grid with no cloud in the loop.

As Spain's Transmission System Operator, Redeia found substation functionality tied to the refresh cycle of the hardware it ran on, because protection and control systems were sold as indivisible hardware and software packages. Using Barbara's platform, the company virtualized the substation oscilloscope as containerized workloads on a thin edge node, sustaining 4,000 sampled values per second at the edge and proving that any less demanding use case could run on the same infrastructure.

With 19 factories across Europe and Africa, GBfoods had no visibility into how energy was actually consumed at process level: the data was locked behind a heterogeneous mix of industrial protocols and could not be accessed remotely. Using Barbara's platform together with AVEVA's edge-to-cloud data stack, the company replaced its SCADA-centric approach with one standardized edge architecture, deployed and managed remotely across every site under IEC 62443-4-2.

With more than 200 water treatment projects across 12 countries, GS-Inima Environment found its operational data locked inside a different SCADA system at each facility, with no historical record to analyse. Using Barbara's platform, the company deployed its first edge nodes in under 12 months, standardizing data flows from plants of different ages and vendors into a single real-time stream shared across the fleet.

Enerclic, a leading energy-sector integrator managing more than 7,000 telemetered units across distributed renewable and grid infrastructure, faced growing operational complexity as its fleet expanded. By adopting Barbara's platform as the standard for new deployments, Enerclic centralized device management, automated operations at scale, strengthened cybersecurity, and enabled customers to manage their own devices with greater autonomy.

Argos, one of the largest cement producers in the Americas, identified the pyroprocess (the most energy-intensive and emissions-heavy stage of cement production) as a critical lever in its journey toward carbon neutrality. To optimize kiln operations, reduce fuel consumption, and lower emissions, the company used Barbara's edge AI platform, enabling real-time decision-making directly at the industrial edge.

Correa Group, a leading Spanish manufacturer of large-scale milling machines, used Barbara's platform to overcome the limitations of traditional IoT solutions, gaining full ownership of its machine data while ensuring operational visibility even without connectivity. Within two years, the company digitized and scaled the solution across more than 70 machines, enabling real-time intelligence and accelerating its transition from a hardware manufacturer to a service-driven business.

With more than 125 years distributing electricity across rural Spain, Aduriz Distribución operated a network built from different manufacturers' equipment, each running a different protocol, in substations with little or no external connectivity. Using Barbara's platform, the company brought two low-voltage substations under a single edge architecture that unified data collection from legacy equipment, secured every transmission and could be maintained remotely without site visits.

Acciona aimed to optimize chemical consumption, improve operational efficiency, and enable real-time predictive intelligence across its desalination and water treatment facilities all over the world. To achieve this, Acciona partnered with Barbara to deploy a scalable Edge AI and Edge Computing architecture that enabled autonomous optimization of industrial applications and Machine Learning algorithms directly at the edge.