Business data was scattered across apps, CRMs, spreadsheets and third-party tools. Reports were stale by the time they reached leadership. We built a real-time data platform — ingestion, warehouse, transformations, live BI and threshold alerts — so the business could stop reacting and start noticing.
The symptoms were classic — the kind every scaling business hits:
Streaming ingestion from every source, a lightweight warehouse with versioned transformations, live dashboards per role, and a threshold-alert engine that pings the right person on the right channel.
Real-time capture from apps, CRMs, payment gateways, ad platforms and 3rd-party integrations.
Columnar store optimised for analytical queries — cost-efficient, scales with the business.
Versioned SQL/dbt-style transformations — one definition per metric, tested and documented.
Role-based dashboards for founders, ops, category managers — refreshed continuously, not weekly.
Alerts on metric breaches routed to the right person on the right channel — with cool-downs to avoid noise.
Every metric has one canonical definition, an owner and a description. No more "which GMV do you mean?"
Role-based access to dashboards and raw datasets — PII masking where needed.
Row-count, freshness, null-ratio, schema-drift checks — with alerts when pipelines silently break.
Sources → streaming ingest → warehouse → transformations → BI & alerts. Each layer swappable, all events auditable.
Stack is chosen per client — the pattern is consistent, the components are pragmatic.
Leadership stopped asking "what happened last week?" and started asking "what's happening right now?" — and the ops team started fixing problems before customers noticed. The debate shifted from "which number is correct?" to "what are we going to do about it?"
We'll help you get from scattered spreadsheets to a live, trusted view of the business.