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Industries Energy and utilities

Energy and utilities

Reliable data for systems that cannot go down.

We migrate billing and customer data without losing history, calculate tariffs you can trust, and run AI in operations where reliability is not optional.

Electricity transmission pylons against the sky
The industry

Where the data lives.

Energy businesses combine very large customer bases, complex pricing and critical infrastructure. Data errors show up as wrong bills, lost customers or operational risk.

Who we work with Billing, pricing, operations and commercial teams.

The data challenge

Where data gets in the way.

Tariffs are complex.

Prices, standing charges and contract terms interact in ways spreadsheets struggle to follow.

Migrations are risky.

Moving billing systems can break customer history and trust.

Finding the right customers.

Business prospects are called before anyone checks they can switch.

Operations cannot fail.

AI has to earn its place on critical systems.

How Jambo Labs helps

What we build.

01

Tariffs and billing you can trust

Calculations rebuilt, tested and reconciled against what customers were charged.

data modelling · reconciliation

02

Migrations without surprises

History moved, checked line by line, and signed off before switch-over.

migration · data quality

03

Customers qualified before the call

Kestrel, our own product, finds and ranks business energy prospects.

Kestrel · lead qualification

Interactive demo

A billing switchover, checked on every account, in 90 seconds.

Every bill of the last year is produced again in the new system and compared line by line. Watch four causes explain the differences, one of them overcharging two thousand customers, and the board sign off on evidence.

A contained demo on invented data. Nothing you do here leaves the page.

Techniques in this demoSystem migrationStep 1, Systems: every account moved to a new billing platform.Parallel runStep 2, Rerun: every bill of the last year produced again in the new system.ReconciliationStep 2: old against new, line by line.Anomaly clusteringStep 3, Differences: differences grouped by their cause.Root cause analysisStep 4, The catch: one group traced to a tariff mapping.
Also possible

Where the same data goes next.

  • Demand forecasting and churn prediction from billing and meter data.
  • Business customers qualified before the call, with Kestrel.
In practice

What our team has done before.

Work our team has delivered across their careers. Clients are anonymised.

AI in production
Live on national infrastructure

AI-driven operational support running on critical national infrastructure, where reliability is not optional.

Data platforms & engineering
Billing migration and tariffs

A billing data migration for an energy supplier, with tariff calculations rebuilt and reconciled.

Where to start

Start with one calculation you do not fully trust. We rebuild it, test it against real bills and show where it drifts.

The two-week diagnostic
Start a conversation

Tell us the report your team rebuilds every month.

No pitch. We will show you what your own records could already do.

Talk through your use case

Photo: jambo-labs.com image library.