One source of truth, ready for decisions.
Data lakes, pipelines and dashboards that put the right number in front of the right person. We start with the decisions you need to make, then build only the data that answers them.
What we ship.
Data lakes and warehouses
One place for data from every system, modelled so it can be trusted.
Pipelines and ETL
Scheduled, monitored, alerting when a source breaks.
BI dashboards
The numbers leadership asks for, refreshed without anyone exporting a CSV.
Reporting automation
Weekly and monthly reports that build themselves.
Data quality
Validation, lineage and the checks that catch bad data before a decision does.
Foundations for AI
Clean, documented data is what makes the AI work later.
Aris AI: live markets, journal analytics and auditable signals.
Tick-by-tick prices, a journal that scores every trade and signal rooms with real track records, on one data platform built by this team.
How a first project runs.
- Week 1Source inventory, the questions that matter, a data model
- Weeks 2–3First pipelines and a working warehouse
- Weeks 4–5Dashboards with the people who will use them
- Week 6Monitoring, documentation, handover
Questions we hear most.
Which tools?
PostgreSQL and AWS by default, Python for pipelines. We fit your existing BI tool when you have one.
Our data is messy. Is that a problem?
It is the usual starting point. Cleaning and modelling is most of the work, and we plan for it.
Can this feed AI later?
Yes. We design the model so assistants and reports draw on the same trusted data.
Your numbers, in one live view.
Three quick questions, then pick a time. An engineer who has built it before reads it the same day.