AnalytxEdge
Problem
Business intelligence is still gated behind specialists. Marketing agencies and SaaS teams pull data from ad platforms, CRMs, billing systems and spreadsheets, then rebuild the same reports by hand every month. Traditional BI tools require a data analyst to model the data and maintain the dashboards, which small and mid-sized companies cannot justify hiring. The new generation of AI chat tools promises to fix this, but they query raw tables with no definition of what a metric means, so the same question returns different numbers on different days. The result is a choice between reports that are slow and expensive, or fast answers nobody trusts enough to act on.
Solution
AnalytxEdge puts a governed semantic layer between the data and the questions. Metrics, dimensions and joins are defined once, with fanout-safe aggregation so numbers stay correct across joined tables. From that single definition, anyone can ask a question in plain language and get a consistent, auditable answer. Dashboards, scheduled reports and client share links are generated from the same model, so what a client sees always matches what the team sees. The platform also exposes its governed layer through a remote MCP server, letting AI assistants like Claude query company data directly rather than guessing at schema. A Chart Studio with sandboxed WebGL runtimes lets teams build custom visualisation types no other BI tool can produce.
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