Query
Control which data each role can read through an agent.
AI across the stack
AI That Works On Your Operation, Not Around It
Fuuz puts AI to work in three ways: for the developers who build on the platform, in the agentic workflows that run your operation, and for the end users who need governed access to your corporate LLM. All three run on governed, modeled data under role-based access control.
From our founder
“I always say no more dashboards! I want actionable insights. I want to be able to solve problems in real time.”
IMTS 2026
Context Is The New Advantage
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.
- One model of assets, orders, lots and processes
- Agents follow typed relationships instead of guessing
- Apps, agents and integrations share one security model
Governed AI development
One Playbook For Every Developer And Every Agent
The Fuuz MCP server includes server docs that tell an agent how to get things done in Fuuz. Every developer's AI works from the same instructions, so the way your team builds is the way everyone builds.
Add your own tools and you add your own documentation with them. Your standards travel with the tools, so everyone uses the platform the way your team wants it used, not the way each person's prompt happens to guess.
- Built-in server docs teach agents how Fuuz works
- Your own tools carry your own documentation
- One governed way of working across every developer
Without a platform vs. on Fuuz
Without a platformEach developer prompts their own way. Results, standards and security vary by person.
On FuuzAgents read the same server docs and use the same governed tools, under the same rules.
ResultGovernance across every developer's AI, not a hope that people follow a wiki.
Role-based by default
Users Reach Only What You Allow
Everything AI-related in Fuuz runs under role-based access control. Users and their agents can query, mutate or transform only what you permit, and only on the data and tenants you choose.
Mutate
Control which records each role can create, change or delete.
Transform
Control which data flows and transformations each role can run.
Data and tenants
Decide which data, and which tenants, each user and agent can touch.
Bring your own agents
Your Agents. Your Knowledge. Every Corner Of Fuuz.
Fuuz does not force a built-in agent on your people. Vendor agents with hard-coded prompts become one more silo, with their own data and their own idea of how your business works.
Instead, Fuuz opens every corner of the platform to your corporate agents: Claude, GPT, Gemini or a model you built yourself. They work from your company's institutional knowledge, under each user's permissions, not from a software vendor's prompts.
- Any corporate agent, connected through MCP
- Every part of the platform available as governed tools
- Your prompts, your knowledge, your rules
Vendor agents vs. your agents
Vendor agentHard-coded prompts, the vendor's context, one more place your data and decisions live.
Your agents on FuuzThe agent your company already trusts, with access to all of Fuuz under the user's own permissions.
ResultOne source of institutional knowledge, not a new silo per application.
Three use cases
AI For Builders, Workflows And Every User
For developers
Full access to the platform for AI-assisted development, with pre-built tools and the freedom to build new ones quickly. You are never limited to the native drag-and-drop designers: build the way you want.
- Pre-built MCP tools for data models, data flows and screens
- Build new tools rapidly on your own connections
- Work in Fuuz for VS Code with agents, or in the visual designers
- Every change follows the same governed lifecycle
Agentic workflows
Embed agent calls in your Fuuz data flows, using connectors to the models you choose, with role-based access control across the enterprise.
- Call agents as steps in your data flows
- Connect frontier, open or home-grown models through connectors
- Role-based access control and policies on every call, at every site
- Triggered by events, traced and audited
For end users
Bring your corporate LLM to your people inside Fuuz, and govern how they use it. Control system prompts, access and usage with role-based access control, straight inside the platform.
- Manage system prompts centrally
- Decide who can use which models and tools
- Control usage across teams and sites
- Answers use only data each user is allowed to see
Open by design
Connect Any AI To Anything You Run
AI-enable anything you connect
Build your own MCP tools on top of your own connections. Every system you connect to Fuuz, on the floor or in the enterprise, can become a governed tool your agents use.
Your enterprise bridge for legacy systems
Got a legacy ERP or another system with no modern interface? Use Fuuz as the bridge, so it can take part in modern AI workflows that are governed and deterministic.
Bring your own AI
Home-grown, frontier or open models: your pick. MCP is universal, and Fuuz's open APIs mean anything can be connected.
At the edge or in the cloud
Run local agents at the edge and connect them to the Fuuz Gateway, or run agents in the cloud with OAuth, so your end users get secure access under their own permissions.
Enterprise agentic development
Vibe-Coded Apps, Enterprise Foundations
AI-enabled citizen developers are solving problems faster than ever. That is great for speed, but apps generated on their own are rarely scalable or secure, and their context disappears when the person who prompted them moves on.
Fuuz is the enterprise agentic development platform. Apps built with AI on Fuuz inherit the Unified Namespace and everything the platform provides, and Fuuz documents them as they are built, so you never lose the context.
You cannot vibe code governance. The platform is the thing your business is missing to finally answer how AI is governed across the company, at least on the development side.
- Inherit the Unified Namespace and the data model
- Inherit security: sign-in, role-based access and audit
- Inherit scalability and platform updates
- Self-documenting as you build
Standalone AI apps vs. apps on Fuuz
StandaloneFast to create, but each one has its own data, security and upkeep.
On FuuzJust as fast, with the UNS, security, scale and updates already in place.
ContextDocumented automatically as you build, so knowledge stays with the company.
Deterministic by design
Straight Answers. No Guessing.
Your agents do the reasoning. Fuuz flows do the work. When an agent calls a typed Fuuz flow, at the edge or in the cloud, it gets the same result for the same input every time, carried out by your business rules.
You define the contract. Every MCP tool you build has its own deterministic input and output schema. Have AI draft it for you, or use the Fuuz Data Flow forms and set it up with point-and-click configuration.
That changes what end users get. Instead of letting an LLM piece together answers across separate systems and databases, give it tools that query the graphed data in Fuuz and run data flows. The answer is a straight answer, and your data team can validate it. See how it works.
- Your own input and output schema on every tool
- Built with AI, or with point-and-click Data Flow forms
- Answers come from graphed data and data flows, not from the model stitching systems together
- Results your data team can validate
- Role-based access on every call, headless or with a person in the loop
An LLM on its own vs. a Fuuz tool
LLM on its ownPulls from separate systems and databases, then infers how they join. Plausible, but not verifiable.
Fuuz toolTyped input, typed output, run by a data flow over the modeled graph. Same question, same answer.
ValidationYour data team can test and sign off the tool, not just spot-check a chat.
Guardrails
AI Governed Like Everything Else
Sign-in and access
Agents connect through OAuth, and every tool call runs under the signed-in user's permissions.
Tool policies
Policies set which tools an agent may use.
Protected data
Agents cannot read fields marked sensitive, such as credentials.
Traceability and audit log
Every change an agent makes is traced to the tool that made it and recorded in the audit log.
AI readiness
AI-Ready Starts With The Data
Most AI projects in manufacturing stall on data: it is scattered, uncontextualized and locked in systems that do not talk. Fuuz fixes the foundation first. Data is connected, persisted and modeled once, so AI starts from information you can trust instead of another cleanup project.
See how this maps to the new layers of industrial technology in the industrial AI stack.
- Contextualized data in one model
- One GraphQL API for every record and application
- Permissions that follow the user into every agent call
Get started
Put AI To Work On Governed Data.
Tell us what you run today and what you need next. We will map how Fuuz fits, without ripping anything out.
Prefer to talk? Call 1-877-801-FUUZ (3889)