EENSEK · AI Workforcebuilt by It's Sorted
Open vacancy · ENSEK is hiring this

Product Manager — Asset Management

Meter estate & smart-rollout PM · vacancy

Here's what AI can do for this role — and what still needs a human. Built straight from ENSEK's own job advert, running live on my_db.ensek_demo.accounts. Not a slide about AI. The job, getting done.

What the AI does

Every line on the left is lifted from ENSEK's actual job ad. If a card lacks a harvested JD line, it is omitted. On the right is the AI doing it — with eligible cards running live against the warehouse and offline inspection clearly labelled in the workspace.

Their job ad asks

“Own the strategy and roadmap for Asset Management, informed by users, retailers and commercial partners”

AI delivers, live

What's the current meter fleet breakdown — tech type by fuel, share of fleet and mean consumption?

bar chart
Their job ad asks

“Define and track key performance metrics (e.g. asset issue rates, MTD processing accuracy, onboarding times)”

AI delivers, live

Which regions have the largest traditional-meter tail — the smart-rollout gap by geography?

bar chart
Their job ad asks

“Conduct user research and bring actionable insights into product decisions and stakeholder conversations”

AI delivers, live

How stale are meter reads across the fleet — mean and worst-case days since last read, by tech and fuel?

bar chart
Their job ad asks

“Run experiments, analyse data, and iterate based on evidence to improve product outcomes”

AI delivers, live

How does the active book split by settlement class — HH vs NHH by fuel and meter tech?

table
Their job ad asks

“Build strong relationships with stakeholders while maintaining a product-led approach and protecting team focus”

AI delivers, live

Which meter-tech band carries the most book value — revenue concentration by asset type?

kpi

What stays human

The honest other half. AI does the analysis; a person owns the decision — especially where regulation, fairness and accountability bite.

How it works

Ask in English

A plain-English question — the same one the job ad describes — is translated to SQL by the agentic backend.

LIVE — computed now against 27.6M rows

Curated cards run server-side against MotherDuck when eligible. The workspace separately labels any local inspection path.

Real data, live

Runs against my_db.ensek_demo.accounts. No synthetic numbers.

Self-falsifying

Each figure carries a falsifier — recomputed from the result set, not a stored number, so it can't quietly drift.

Where it plugs in

Function / Ignition surface: Fleet · Smart rollout · Read quality · Settlement · Asset value. Grounded in the real ENSEK: Ignition — a real-time, event-driven meter-to-cash SaaS platform for energy suppliers · 7M+ accounts · regulated by Ofgem.

Watch it do the job — for real

It's the role getting done: curated questions run live server-side against the warehouse; local inspection is labelled inside the workspace.

Open the live workspace →

Provenance. Representative ENSEK-style operational dataset (480 accounts · 728 meters · 5,676 monthly consumption records). Schema mirrors my_db.ensek_demo.accounts and my_db.ensek_demo.meters. Seed 20260609 — reproducible. No real ENSEK or customer data.

It's Sorted — I took ENSEK's job ads and didn't write a report on what AI could do. I built it. Get the rest sorted →