ThinkDebug
Practical deep dives on software architecture, AI systems, and scaling digital products - drawn from the work we ship.
Pipelines, warehouses and dashboards that turn scattered operational data into decisions.
Most reporting problems are not dashboard problems. We build the pipelines and definitions underneath, so revenue means the same thing in two departments and the number does not change depending on who exported it.
Most reporting problems are not dashboard problems. We build the pipelines and definitions underneath, so revenue means the same thing in two departments and the number does not change depending on who exported it.
Moving data out of the systems that own it, on a schedule, with failures that are visible rather than silent.
A modelled layer with agreed definitions, so a metric has one meaning across the business.
Built with the people who will use them, around decisions rather than around available fields.
Event tracking designed deliberately, so you can answer questions you have not thought of yet.
Tests, freshness checks and ownership, so a broken pipeline is caught before a decision is made on it.
Bringing scattered spreadsheets and legacy reporting into one place without losing history.
Not sure which approach fits? A 30-minute call usually settles it.
Talk to an engineerMost of our work comes from clients we already shipped for. These are the reasons they give.
We agree what a metric means before building anything that displays it.
Freshness and quality checks in the pipeline, so nobody presents a stale number.
Models and transformations live in a repository and are reviewed like any other code.
Dashboards designed alongside the people who will act on them, not delivered to them.
One decision supported properly beats a warehouse nobody queries.
Warehouse choices that match your actual volume, not a platform bought for a scale you do not have.
The parts clients ask about after the demo: who owns the output, who has access to what, and what happens once data engineering & analytics is delivered.
Send us the scope and we come back with an itemised estimate - no discovery fee, no obligation.
We have shipped data engineering & analytics in these sectors before, so we already know where the regulatory, integration and scale problems tend to hide.
Tell us about your industryMulti-tenant platforms, billing and SSO integrations.
Storefronts and checkout tuned for conversion at scale.
Payments, KYC and ledgers built to withstand audit.
ERP, MES and shop-floor telemetry connected to the systems that already run the plant.
Fleet, warehouse and tracking systems that stay accurate when volume spikes.
Patient portals and clinical tools built to compliance.
See the full list and the work behind each one.
Explore all industriesChosen for fit and long-term maintainability, never for novelty.
Getting data out and in.
Where the modelled layer lives.
What the business actually opens.
Transparent stages, with something you can look at from the second one onward.
Which decisions need data, and what would change if the number changed.
Agreed in writing before anything is built.
Extraction, transformation and a modelled layer under version control.
Built with the people who will use them.
Freshness, volume and consistency tested automatically.
So your team can extend the models without us.
Let's start with you.
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Still have a question we have not answered?
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Tell us which decision is being made badly and we will trace the number back to where it breaks.
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