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

LIMS Product Manager

Regulated lab software product manager

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.fisher_demo.lims_events. 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

“exception backlog by module and validation state — the PM's primary queue health signal for regulated release gates.”

AI delivers, live

How is the exception backlog distributed across modules and validation states — where are the Pending and Failed items that block regulatory release?

bar chart
Their job ad asks

“throughput by event type — pipeline balance signal for capacity planning and bottleneck identification.”

AI delivers, live

What is the event throughput mix across the LIMS workflow — are sample processing steps balanced or is one step creating a bottleneck?

bar chart
Their job ad asks

“SLA breach rate by module and user role — the quality signal the PM tracks against regulatory and customer SLA commitments.”

AI delivers, live

Which modules and user roles have the highest error rates — where is the SLA breach pressure most acute?

table
Their job ad asks

“change request pipeline — INFERRED from regulatory obligation framework (ICH Q10, GAMP 5 change control). Validation runs are the regulated gating mechanism for every LIMS change.”

AI delivers, live

What is the shape of the change request pipeline — how many ValidationRun events are pending vs completed, and which modules have the deepest change backlog?

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.fisher_demo.lims_events. 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: Exception backlog · Throughput · SLA · Change control. 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. Offline path: SYNTHESISED labelled 3,000-row LIMS event log (ITS-169, seed 20260611). Schema mirrors my_db.fisher_demo.lims_events. NOT real operational data. Live path (dormant): server-side MotherDuck query against fisher_demo.lims_events.

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 →