The Avigna AIOT Suite: Connecting Edge, Cloud and Field Intelligence

Industrial organizations have spent years connecting equipment, collecting telemetry and building operational dashboards. The next challenge is not simply increasing the amount of data available. It is creating a coherent intelligence architecture through which equipment, applications and people can work with the same operational context.

An OEM may need to collect data from machines, process it locally, analyze it centrally, provide AI-assisted service and build digital experiences under its own brand.

These requirements are connected. Yet they are often addressed through separate products, platforms and integration layers.

The Avigna AIOT Suite is designed around a different proposition: one connected intelligence architecture spanning edge, cloud and field.

It brings together AvignaCube™, AvignaAIEdge™ and AvignaTechnicianCoPilot™ through a shared data and intelligence backbone.

“Industrial intelligence reaches its full value when the edge, the cloud and the field operate as one connected system, continuously exchanging data, context and action.”

The Case for a Connected AIOT Architecture

The traditional industrial technology stack often separates device connectivity, data processing, analytics and service applications.

That separation can create operational friction.

Data collected from equipment may remain isolated from technical documentation. Service tools may not have access to the full asset history. AI applications may be built independently, without a shared knowledge model. Edge devices may operate locally without contributing their insights to the wider enterprise.

The result is a fragmented intelligence landscape.

The Avigna AIOT Suite addresses this through three complementary products:

• AvignaCube: The AI-native AIOT data platform on Microsoft Azure.
• AvignaAIEdge: Edge hardware and software for data collection, machine learning and local AI.
• AvignaTechnicianCoPilot: A mobile AI copilot for field service and maintenance technicians.

The suite is designed so that these experiences share one data and intelligence foundation.

AvignaCube: The Cloud Intelligence Foundation

At the centre of the suite is AvignaCube, an AI-native AIOT data platform built for equipment OEMs and enterprises.

It ingests, contextualizes and reasons over structured, unstructured and multimodal data from connected equipment. Its capabilities include device management, unified data ingestion, knowledge graphs, retrieval-augmented generation, agentic orchestration and natural-language access.

The platform is designed to help OEMs move beyond basic monitoring into contextual intelligence, predictive analytics, generative AI and agentic decisioning.

What Makes AvignaCube Different?

Its architecture treats AI as a core platform capability rather than an add-on.

The knowledge graph models assets, components, sites, faults and procedures as connected relationships. RAG and vector search support grounded answers. Multi-agent orchestration enables workflows that can investigate, correlate, recommend and act within approved guardrails.

This provides the foundation for applications such as predictive maintenance, AI-assisted diagnostics, natural-language data queries and digital service experiences.

AvignaCube is also designed for OEM requirements, including white-labeling, multi-tenancy, extensibility and enterprise scale on Microsoft Azure.

AvignaAIEdge: Intelligence Where Equipment Operates

The cloud provides centralized intelligence. Industrial operations also require intelligence at the source.

AvignaAIEdge extends AvignaCube’s architecture to the equipment itself through hardware and software designed for industrial data collection, machine learning and local AI inference.

It is available in two hardware tiers.

Core provides protocol translation, data collection, rules-based processing and lightweight ML inference.

GPU (AI+) adds local LLM and SLM inference, computer vision and generative AI at the edge. It supports use cases such as offline copilots, video-based inspection, voice-guided assistance and generative diagnostics.

This architecture is relevant when industrial intelligence must operate with low latency, limited connectivity or local data processing requirements.

The edge product supports store-and-forward synchronization, local decisioning and remote management through AvignaCube.

Its role is not to replace the cloud. It is to extend intelligence to the environment where the equipment operates.

AvignaTechnicianCoPilot: Intelligence in the Hands of Technicians

The final part of the suite brings AI into the field and plant service environment.

AvignaTechnicianCoPilot is a mobile AI copilot that uses AvignaCube’s knowledge graph, telemetry and generative AI to support troubleshooting, documentation lookup, visual diagnostics, guided repair and digital service logging.

Its workflows include conversational fault diagnosis, cited manual and SOP search, photo-based asset lookup, context-aware copilot chat, service history access and parts identification.

The product addresses a practical challenge in industrial service: technicians need information that is relevant to the asset, the fault and the task in front of them.

A generic AI assistant may provide an explanation. A service copilot grounded in asset history, telemetry and technical documentation can support a more contextually relevant workflow.

The knowledge capture loop also allows technician resolutions to feed back into the AvignaCube knowledge graph, helping improve diagnostic knowledge across the workforce.

How the Three Products Work Together

The suite’s architecture can be understood as a continuous intelligence flow.

AvignaAIEdge collects data and generates local insights. AvignaCube provides centralized data, knowledge and AI services. AvignaTechnicianCoPilot brings that intelligence into the hands of technicians.

The relationship works in both directions.

Edge-generated insights synchronize into the same knowledge graph as cloud-processed data. Models trained centrally in AvignaCube can be pushed back to GPU-tier edge devices.

Technician resolutions can also feed back into the knowledge graph, improving the diagnostic foundation for future service workflows.

This is the intelligence flywheel described in the product blueprint.

It is not simply a collection of three products. It is an architecture in which data, intelligence and operational knowledge can move across the edge, cloud and field.

Built for OEMs and Industrial Enterprises

The suite is designed for organizations that need to digitize their installed base without becoming software platform companies.

Equipment OEMs may operate across multiple product lines, geographies and regulatory environments. They may also need to provide after-sales service, warranty support and digital experiences under their own brand.

The Avigna AIOT Suite addresses these requirements through its shared architecture.

AvignaCube provides the platform foundation. AvignaAIEdge extends intelligence to industrial environments. AvignaTechnicianCoPilot connects that intelligence to service operations.

Together, they support use cases across manufacturing, smart buildings, energy and utilities, remote monitoring and service, predictive maintenance and digital twins.

The AvignaAIoT Suite Difference

The strategic value of an AIOT architecture lies in the relationship between its components.

A cloud platform without edge intelligence may struggle with offline and low-latency requirements. Edge devices without centralized intelligence may create disconnected operational silos. A technician application without contextual equipment knowledge may remain limited to document retrieval.

The Avigna AIOT Suite is designed to address these gaps through a common intelligence backbone.

Its proposition is that industrial organizations should be able to connect equipment, build AI-driven applications, operate intelligence at the edge and empower technicians without assembling three disconnected technology stacks.

Looking to build a connected industrial intelligence architecture?

Explore the Avigna AIOT Suite and discover how AvignaCube, AvignaAIEdge and AvignaTechnicianCoPilot can support your connected equipment, edge AI and field service requirements.

Talk to Avigna.AI about building your AI-native, Azure-native industrial intelligence strategy.