cashcrown // ai.data
a single source of truth.
You need “analytics dashboards”, but building it in-house gets stuck on integrations, maintenance and lack of time — and the result tends to be fragile and hard to scale.
At Cashcrown, we build dashboards using data from your systems: ERP, CRM, SQL databases, spreadsheets. Each metric has a documented methodology: its source, calculation method, and potential inaccuracies. Sensitive data is masked at the pipeline level (PII) before reaching the visualization layer.
Where numbers require business context or decisions are irreversible, we design human-oversight: the dashboard flags anomalies, but conclusions are drawn by the person responsible for the outcome.
We agree on sources, legality and the target data schema.
Acquisition → normalization → dedup → validation, repeatably.
Embeddings + semantic search; RAG over the results.
Rank tracking in Google and AEO; trends over time.
We work within ranges depending on the number of data sources and pipeline complexity. We start with a pilot for one view with a narrow scope so you can see the value before a larger investment. When a dashboard replaces several hours of manual data collection weekly, ROI appears within a few months. You can calculate the exact return using the ROI calculator; we don’t provide upfront pricing because it depends on the actual scope.
Yes. We connect to sources via controlled, documented connectors. PII is masked before processing, data doesn’t leave the environment without consent, and retention and access are controlled in line with GDPR. If the pipeline processes personal data automatically at scale, we indicate the need for a DPIA. AI Act requirements are incorporated from the start of the design.
With an audit of available data and one view with a measurable goal: what it should display, who makes the decision, and how we’ll verify the dashboard’s usefulness. We show a working prototype before asking for trust, then expand the scope. More on our approach: how to choose the first process.