Asset performance monitoring
Generation, availability and downtime per asset in one view, normalised across the mix of inverters and turbines you actually own.
Monitoring, forecasting and reporting across a portfolio, so performance, downtime and yield are one number rather than a spreadsheet for every site you own.
Talk to our energy team
One senior pod across the asset data, the forecast and the report, so a portfolio is understood the same way whether it holds four sites or four hundred.
Four outcomes agreed as measures before the build starts, and reported against once it ships.
Every site reports the same way, so performance is comparable without a reconciliation first.
Underperformance surfaces as an alert with a work order, not as a gap noticed at month end.
The investor pack comes from live data, so quarter end stops consuming a week of somebody's time.
Runbooks, access and a recorded walkthrough at handover, so your team is not dependent on ours.
Three things decide whether an asset platform earns its place, or becomes another dashboard beside the spreadsheets.
Portfolios are rarely one manufacturer and one vintage. We normalise across what you actually own rather than what a vendor platform prefers you owned.
When the investor pack and the maintenance queue disagree, both get distrusted. They are built from the same data here, so they cannot.
Repositories, cloud accounts and documentation sit in your name from the first commit. Leaving should cost you notice and nothing else.
Four stages from first conversation to a platform your own team runs. Every engagement passes the same gates, with data quality tracked from day one.
What each site already reports, where the formats diverge, and which numbers the operations team and the investors are each judged on.
You get: A site reporting audit and the scope of the normalised model
A normalised model across the fleet you actually own, reviewed with the people who will be reading it at seven in the morning.
You get: The fleet data model, reviewed with your operations team
Senior engineers shipping in short cycles you can watch, with read paths and network segmentation in place from the first commit.
You get: Working software every cycle, with read paths proved
Data quality testing against known site output, a security review, then a phased rollout site by site with runbooks and a support window.
You get: Data quality results, a security review and runbooks
It is the normal case. Normalising a mixed fleet is most of the work, and we model against what you actually own rather than asking the portfolio to look like a vendor platform expects.
No. We start from read-only paths and stay out of anything that controls an asset. Where a write path is genuinely required, it is designed with a rollback and proved on one site first.
Yes, and from the same data operations uses. When the investor pack and the maintenance queue come from different sources, both end up distrusted, so they share one source here.
Yes. Work orders and evidence capture run offline at a site with no coverage and reconcile as soon as there is any, because that is the condition most of this work actually happens in.
Yield forecasting and underperformance detection trained on your own history, always with the confidence interval shown. A single hopeful number is worse than no forecast at all.
You do, from the first commit. Repositories and cloud accounts are created inside your organisation, and nothing we build is licensed back to you or shared between clients.
Industrial platforms and back-office automation delivered in sectors that run on the same problems.
Tell us how many spreadsheets stand between a site and the board pack, and a senior engineer will come back to you within one business day.
