Bring energy expertise
to your AI agent
Add the Ento connector to the AI tool you already use via our MCP server, such as Claude, ChatGPT, or Cursor. Then just write what you need from your energy data
- Upload and manage energy data, sites and meters
- Analyse and monitor energy performance across the portfolio
- Work with weather data and building information connected automatically
- Verify projects with automated IPMVP M&V
- Set up workflows: instructions that run on a schedule across all your buildings
Kingsway School is set up with 3 meters and opening hours. Across the portfolio 14 of 240 sites run more than 30% outside opening hours. Elmwood School is the worst at +47%, with an increase in consumption of around 45.000 kWh a year.
Claude
ChatGPT
Cursor
Your AI tool works on live meter data
Every reading comes off a real meter in a building you run, corrected for weather and modelled against that building's own history. Here is what it can do.
Find the energy waste before the site visit
Every building is measured against its own baseline. We adjust for local weather so sudden temperature shifts don't trigger false alarms. What you get is a list of real issues, each backed by the exact kWh, cost, and carbon impact.
- Baseload, peak, profile and schedule
- Compared inside your portfolio or against peers
- 50+ benchmark metrics per site
All your meters in one place
Ento pulls meters from national data hubs, utility APIs, submeter providers, vendor protocols and manual uploads across Europe and beyond. Sites, areas, usage types and opening hours live in the same place as the readings. There is no hardware to buy and nothing to install.
- Electricity, heat, gas and water
- Virtual and aggregate meters
- Gaps filled, weather attached
Prove the saving actually happened
Register a project and Ento keeps modelling what the building would have used without it. The saving is tracked against a weather- and calendar-normalized baseline model. Every step follows IPMVP and established international M&V standards.
Evidence collected as you go
ISO 50001 evidence, energy performance certificate changes and stakeholder reports are built from the meter data you already have. Ento gathers the evidence as the year runs and keeps it current, so everything is ready whenever the audit is happening.
Your method on a schedule
You already have a way of screening a portfolio. Write it down once, in plain language, and it becomes a workflow: a set of instructions that runs on a schedule across all of your buildings until you change it. You stay in the loop where it matters.
Site names and figures in the illustrations are examples.
What early testers are building
Most people start with whatever manual task wastes the most time each week. These are the asks that come up most often.
Drift picked up overnight, ranked and waiting when you sit down.
Your screening method, written down once and run on every building you hold.
Sites created and meters allocated in an afternoon instead of a fortnight.
Consumption split per tenant on the billing cycle rather than by hand each quarter.
Benchmark an acquisition against its peers while the deal is still open.
Consumption, comparison and the likely cause while the client is on the line.
Some of the people testing this have a product of their own.
The Ento connector sits underneath it, so your customers get your interface while Ento processes the data across all buildings and workflows.
Tell us what you want to build
Early access is open and we are letting people in a few at a time. Tell us about your portfolio and what you want to do with it, and we will get you connected.
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Still got questions?
The practical ones. Security and permissions are covered above. If yours is not here, ask us when you sign up.
The same thing. MCP (Model Context Protocol) is the standard way AI tools like Claude, ChatGPT and Copilot connect to outside systems. For you it is simply a connector: you add Ento once in your AI tool's settings, and from then on that tool can use all your Ento data and analysis while you work.
Your energy data does need to run through Ento, because that is where meters are allocated and the models are built. You do not need an existing subscription to get there. If your organisation already uses Ento your access follows your login. If not, sign up for early access and we will get your data in.
Nothing during early access. We are opening it up in batches to learn how people actually use it, and we would rather find that out with you than guess. Pricing comes later, and everyone in early access hears about it first, well before anything changes.
Claude, ChatGPT, Cursor and Copilot all work today, along with any other AI tool that supports MCP connectors.
Two things: an Ento login and an AI tool that supports connectors, such as Claude, ChatGPT, Copilot or Cursor. Many organisations already have one through their Microsoft or Google licence. If you do not have one yet, tell us when you sign up and we will help you get started.
It does not really depend on the country. Where there is a national data hub or a utility integration the meters connect on their own, which today covers Denmark, the UK, France, Spain, Italy and a number of other markets. Everywhere else you hand over a CSV or whatever export your utility gives you, and the sites and meters are built from that.
Handing over a CSV is fine as a way in, and it is often how a portfolio starts. The difference is what happens to it. In Ento the readings are allocated to meters, corrected for weather and modelled against each building's own history, so your agent can keep asking and the answers hold up. A file pasted into a chat window is a snapshot with nothing behind it.