Current because the work happens there
When production, inventory, quality and maintenance run on Fuuz, every transaction lands in the model as it happens. The context is not copied from somewhere else, so it does not go stale between syncs.
The industrial AI stack
After IMTS 2026, IoT Analytics described a new, AI-led industrial stack forming above the ISA-95 pyramid: industrial DataOps, a knowledge graph, interfaces such as MCP, agents, and apps where people stay in the loop. Most manufacturers would have to buy and integrate each layer. On Fuuz, most of them are one governed platform.
Where Fuuz fits
Each layer of the new stack, top to bottom, and what it means in Fuuz.
Operator, supervisor and engineering apps built on Fuuz, with approvals and electronic records in the workflow.
Your corporate agents, such as Claude, GPT, Gemini or your own, reach every part of Fuuz through MCP. Agent calls can also run as steps in data flows, traced and audited.
MCP tools, pre-built or your own, one GraphQL API for every record and application, and the industrial and enterprise protocols your systems already speak.
One data model with an ORM that turns your data into a knowledge graph across the plant, ERP, PLM and CRM.
Run MES, WMS, QMS and CMMS on Fuuz, or keep the ones you have, with history stored in Fuuz for most use cases. ERP and PLM connect two ways.
Connectors, data flows and an enterprise Unified Namespace that persists state and context, not just messages.
The Fuuz Gateway is a native part of Fuuz, not a third-party add-on: a software-defined gateway at each site with edge connections, data flows, a local UNS and local agents, outbound-only.
PLCs, sensors, robots, scales and scanners connect through the Fuuz Gateway. Nothing on the floor is replaced.
Why it matters
The clearest signal from IMTS 2026 was where value is moving: away from tools that only move data, toward platforms that own its context. Vendors told IoT Analytics that the data model and the knowledge graph are what set them apart, and even hyperscalers now argue for connecting and contextualizing data where it lives instead of pooling it in one lake.
That is the layer Fuuz was built around. Data is connected, persisted and modeled once, and every app, agent and API works from that same model, under the same security. And in Fuuz, that model is more than a map of your data: it is the backend your applications run on.
The stack, two ways
Not just the graph
Most knowledge graphs sit beside the systems that run the business, as one more integration point. Fuuz is where your applications actually run. That is why its context is the most valuable in the stack.
A graph beside your systems
Fuuz as your application backend
Why it matters
When production, inventory, quality and maintenance run on Fuuz, every transaction lands in the model as it happens. The context is not copied from somewhere else, so it does not go stale between syncs.
A graph fed by integrations has to be rebuilt every time a source system changes. In Fuuz, apps are built on the model, so the context stays intact as systems around it are upgraded, replaced or added.
Your agents do not just read a picture of the operation. They work through the same data model, business rules, permissions and audit trail as your apps, so an action taken by an agent is as governed as one taken by a person.
Extend the model once and every app, dashboard, API and agent can use it. Teams stop rebuilding the same context for each new tool.
Deterministic by design
Agents are powerful, but on their own they guess. In Fuuz, agents do the reasoning and Fuuz flows do the work: typed, governed and repeatable, at the edge or in the cloud. That is what makes agents safe for any industrial scenario.
Your agent
Decides what to doClaude, GPT, Gemini or your ownRole-based access
Checks who is askingOnly the data and tools that user may useFuuz flow, edge or cloud
Decides how, the same way every timeTyped inputs, typed outputs, your business rulesHeadless or headed
Runs on its own, or waits for a personApprovals where you want them, audit everywhereHow it works
When a tool is typed, a Fuuz flow returns the same result for the same input, every time. The agent chooses what to ask. The flow decides how it is done, by your rules.
Agents can act only on the data, tools and context you expose to them. Nothing else in the platform is visible to them.
Every tool call runs under the signed-in user's role and permissions, with tool policies on top, and every change is recorded in the audit log.
Flows run where the work is: on the Fuuz Gateway next to the machine, or in the cloud. Agents get the same deterministic behavior in either place.
Run fully automated, event-triggered operations, or keep a person in the loop to review and approve inside a Fuuz app. You choose per process.
Because the outcome is governed by typed flows and permissions, agents can take on real industrial work, from a quality hold to a work order, without guessing.
What buyers need to know
Some vendors build in their own agent with hard-coded prompts. Every one adds another silo. Ask whether your corporate agents can reach the whole platform, using your company's knowledge instead of the vendor's.
Eight layers bought from eight vendors means eight data copies, eight security models and dozens of integrations to keep alive. Every seam is where context gets lost and projects stall.
An MCP server is only as good as what sits under it. Ask whether it exposes a real data model and relationships, whether agents can write back or only read, and whether every call runs under the user's own permissions.
Context is becoming the most valuable layer in the stack. Know whether your model of assets, orders, lots and processes lives with you, or inside a vendor's product or a hyperscaler's service.
Engineers will not trust an agent they cannot check. Plan approvals, traceability and audit from the start, so every agent action can be reviewed, explained and reversed.
Shop-floor software decisions increasingly sit with the CIO. Identity, access, data residency and change control decide whether a pilot ever reaches a second plant.
MCP, APIs and proven industrial protocols work today. AI-specific standards such as A2A (agent to agent) and MHS (hardware access for models) are still early. Build on what works now, on a platform that can take on new standards without a rebuild.
Vendors differ: some include AI and MCP access, others plan to charge for it. Get it in writing before your agents depend on it.
Most industrial AI projects stall on scattered, uncontextualized data. Connect, persist and model it once, and every layer above it gets easier.
A practical path
Step 1
Connect machines and enterprise systems through the native Fuuz Gateway and connectors, and define your data model once. That model becomes your knowledge graph.
Step 2
Run MES, WMS, quality and maintenance on Fuuz, or keep what works. Either way, every app works from the same model.
Step 3
Turn data, flows and connected systems into MCP tools and GraphQL queries, under role-based access and tool policies.
Step 4
Embed agents in flows and apps, keep humans approving the decisions that matter, and audit every change.
Questions
It is a way to describe the layers manufacturers now need above and beside the classic ISA-95 pyramid: industrial DataOps, a knowledge graph and ontology, interfaces such as MCP, AI agents, and applications where people stay in the loop. The framework on this page is adapted from IoT Analytics' IMTS 2026 recap.
No. ISA-95 still describes how plants and enterprise systems are organized, and Fuuz works within it. The new layers sit above and beside that foundation, and Fuuz provides most of them on one platform.
No. Fuuz connects two ways to ERP, PLM and other systems of record. You can run MES, WMS, quality and maintenance on Fuuz, or keep the systems you have and connect them.
Yes. Fuuz includes pre-built MCP tools, and you can build your own on top of any connection. Agents connect through OAuth, every tool call runs under the signed-in user's permissions, and every change is recorded in the audit log.
A standalone graph is fed by integrations and is only as current as its last sync, and it has to be remapped whenever a source system changes. Fuuz is also the application backend: MES, WMS, quality, maintenance and the apps you build read and write the model directly. The context is created as the work is done, and it stays intact as other systems are upgraded.
Fuuz has a data model with an ORM layer from day one. That ORM turns your data into a knowledge graph that spans the plant and connected systems such as ERP, PLM and CRM, so agents follow typed relationships instead of guessing.
When the work is done through a typed Fuuz flow, yes. The agent decides what to ask, and the flow returns the same result for the same input every time, by your business rules, at the edge or in the cloud. Agents can act only on the data and tools you expose, under role-based access, headless or with a person approving.
Both at the edge and in the cloud. Local agents can connect to the Fuuz Gateway at a site, and cloud agents connect with OAuth so users get secure access under their own permissions.
Get started
Talk to our team about where your stack is today, which layers you already have, and what Fuuz can take on.
Prefer to talk? Call 1-877-801-FUUZ (3889)