Introducing Qatium AI Build Studio

A governed environment for turning water network expertise into working apps and workflows on top of Qatium — in plain language, inside Qatium itself.”

Water utilities did not become software-heavy because they wanted more software. They did it because every operational need gradually became a separate tool: modeling in one place, telemetry in another, leak workflows somewhere else, plus integrations and spreadsheets to stitch everything back together.

The biggest cost of that model is not license fees. It is latency. A new need appears, a team sees a better way to work, and then the usual cycle begins: scope it, budget it, procure it, integrate it, map the data, and train the team. By the time the solution arrives, the need has often moved on.

At Qatium, we have been reducing that gap step by step.

At the beginning of 2024, we opened our Software Development Kit (SDK) to developers after already spending two years building on top of it ourselves. That gave utilities, consulting firms, engineering partners, IoT providers, and other vendors a real foundation to build on. Many started creating their own layers of intellectual property on top of Qatium: plugins, custom workflows, integrations, interfaces, and utility-specific operational tools.

In 2025, we launched our Model Context Protocol (MCP) so partners and more advanced users could use tools like Claude Code and Codex to build apps on top of Qatium in record time. That made development much faster, but it still required technical fluency. It was a major step forward, but not yet something every utility team could use directly.

AI Build Studio is the natural next step.

Play Video

Today, we are introducing Qatium AI Build Studio: a governed software-building environment inside Qatium that lets teams create apps and workflows in plain language, on top of the same platform they already use for operational work.

Not by starting another software project. Not by exporting data into a generic AI tool. Not by waiting for a roadmap item.

By describing what you need, testing it against network reality, and shipping it inside the platform.

From idea to operational software

The most valuable tools in water are rarely generic. They are specific to each network, each team, and each way of operating.

One utility may need a leak triage workflow that ranks incidents by likely service impact. Another may need a pressure management view that identifies the right assets and visibly depicts  their settings. Another may need a clearer way to visualize closed valves, pipe diameters, or the likely impact of an isolation.

These are often not large products. They are focused operational tools that would make daily work faster and more understandable  if they existed. The problem is that even a small app has traditionally required coding skills, developer time, budget approval, and patience.

AI Build Studio shortens that path dramatically.

You start with a plain-language request. AI Build Studio drafts the app or workflow on top of Qatium’s platform primitives, generating the interface, connecting the right operational context, and structuring the logic for the task. The result is inspectable, so teams can review, refine, and govern what gets built before it is shared or deployed.

The point is not simply that AI can generate code. It is that operational needs can become working software fast enough to matter.

Built on the utility’s trusted platform

AI Build Studio carries weight because it does not build in a vacuum.

Every app starts from the same foundation Qatium already provides: the utility’s digital replica, with a full hydraulic model, whether built from a simple GIS through a drag-and-drop experience or from a fully connected operational stack linked to existing models, SCADA, live data, and external sources in almost any format. That foundation combines asset relationships, geospatial context, advanced hydraulics, simulation tools, and network optimization engines all in one environment.

That means teams do not need to wait for a multi-year transformation before they can build useful software. They can start with very little, connect more over time, and go from their first version of a digital twin to a fully deployed operational stack in days, not months or years.

Because every app is built on top of that same foundation, it stays grounded in how the network actually behaves, not in a generic AI layer disconnected from operations.

Governed by design

AI Build Studio brings software-building capability inside Qatium itself, with the same trust boundary utilities already use for operational work.

It respects the same parameters the platform is designed around: per-utility isolation, data sovereignty, least-privilege access, permission-scoped execution, audit trails, review gates, and the ability to choose the model path that fits each utility’s governance requirements, from advanced frontier models to local models running inside approved infrastructure.

The goal is not only to make building faster. It is to make it faster without letting anything drift outside the platform’s security and policy boundaries, and without letting fragile tools or unsafe logic break operational reality.

Early research preview

AI Build Studio is launching as an early research preview.

We are opening access first to a limited group of utilities, partners, and water network teams so we can learn from real operational use, refine the experience, and expand supported workflows in the right order. Not every use case will be covered from day one, and some patterns will require tighter controls or broader validation before they are ready to scale.

But the direction is clear: once a platform is already inside a utility’s trust, policy, and security boundaries, the path from operational need to working software should take hours or days, not months. It should take a clear idea, the right governed environment, and a system built on network reality.

That is what AI Build Studio is for.

It should take a clear idea, the right governed environment, and a system built on network reality.” 

Interested in early access to Qatium AI Build Studio?

Explore our digital water success stories and visit qatium.ai to learn more about the AI Water platform.