MOTIS.GROUP
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Data infrastructure that catches its own mistakes
I build data platforms for companies that run physical things: pipelines, warehouses, reporting. Then I leave checks in your cloud account that fire when something drifts, an agent that works out why and drafts the fix, and I review every change before it merges.
Start here →Data engineering · Business intelligence · Analytics, for operators of physical assets
An ERP go-live pushed a warehouse’s development compute up 842 hours in a week. The query history said 81% of it was scheduled model rebuilds colliding with everything else. The fix was lanes and schedules.
What I deliver
Build the platform. Leave the thing that watches it.
Most data teams drown in maintenance, and most consultants price by the month and stay. I do neither. The build is fixed price, quoted before anything starts. What stays behind is software that checks the work. I leave.
01 — Autonomous operations
A pipeline fails at 3am: the agent in your account diagnoses the root cause, writes the fix, runs the tests, and opens a pull request. The warehouse bill spikes: it finds the queries responsible and proposes the fix. Nothing merges on a model's say-so.
↳ A platform that fixes itself, in your account, on your stack.
02 — Data engineering
Pipelines, modelling, and infrastructure on dbt, Snowflake, Airflow, Terraform, or whatever you already run. Deterministic at the edges, judgment in the middle, lineage and tests from day one.
↳ A warehouse you can hand over, with no one person holding it up.
03 — Business intelligence & analytics
Semantic layers, dashboards, and metrics that trace to source systems, not to another spreadsheet. Numbers you can put in front of a regulator or a board.
↳ Every figure defensible from dashboard back to source.
The method
Code senses. Agents judge. Code acts.
Everything on a schedule or a trigger is deterministic code. The model sits in the middle, where judgment lives, diagnosing and drafting. And nothing material merges without my sign-off. Speed from the machine, accountability from a person you can name.
Autonomous
Agents diagnose, fix, verify, and open the PR before you wake.
Reviewed
I sign off every material change. Nothing merges itself.
Accountable
Measured on your systems: incidents that never paged anyone, spend that came down, checks that fired.
Industries
Built for operators of physical things.
The flagship practice is electricity distribution. The same discipline travels to any operation where the assets outlive the systems that describe them.
Flagship — Electricity distribution
Operational data verified from SCADA historian to AER submission: availability the historian will back, derating signatures explained, capex justification the regulator will fund.
- Energy networks
- Data centres
- Industrial plant
- Mines
- Water
Who calls me
Always at a moment. Never in steady state.
Someone left, or is leaving
The person who catches the mistakes is walking out the door, and what they know never reached the asset register.
You got caught out
A number was wrong and somebody outside saw it first: a customer, an auditor, a regulator.
It is slowing you down
You are the last check on your own reporting, and it costs you a week every month.
The bills keep growing
The warehouse spend doubled and nobody can say which queries did it.
If the problem is real, let's talk about it.
I don't do capability presentations. Describe the pipeline that keeps failing, the bill that keeps growing, or the check that lives in one person's head, and I'll tell you whether I can help.
Get in touch →William Marzella, Melbourne — hello@motis.group