Reads the assets you already have.
Schema, query history, BI assets, and documentation become the starting point. No blank taxonomy project.
Learns Your Business
Your business context should not reset every morning.
Spotonix learns from your existing analytical work and turns validated concepts into a Context Graph that compounds with every question.
What Learns Means
The system starts from the work your analysts already did.
Most AI analytics tools start with a prompt and guess from there. Spotonix starts with your warehouse, query history, BI assets, and team vocabulary, then turns repeated analytical concepts into reusable business context.
Finds recurring business concepts.
Spotonix identifies useful Segments and Calculations from real analytical work, then makes them available for reuse.
Keeps provenance attached.
Every discovered concept can point back to where it came from, who validated it, and where it was reused.
Improves with every accepted answer.
Validated interpretations become durable context, so the next question can build on what the team already proved.
Learning Workflow
From existing work to reusable context.
Learning is not a magic claim. It is a workflow: ingest the assets, identify repeated analytical ideas, validate them, and keep the accepted logic available for the next question.
Connect read-only sources.
Spotonix starts with the warehouse, query logs, and BI files your team already depends on.
Extract business building blocks.
The system detects repeated entities, measures, filters, and time comparisons as candidate Segments and Calculations.
Validate once, reuse often.
Your team accepts, edits, or rejects the concepts. Accepted logic becomes reusable business context.
context.learn
Source Store sales + customer history
Existing analytical work is read as signal, not thrown away.
Discovered Segment Habitual Buyers
A repeated business idea becomes a named reusable concept.
Compounding Context Question 100 builds on question 99
The graph gets denser instead of resetting with each chat.
Why It Matters
Learning is the part that makes the 100th question easier than the 10th.
Less manual modeling up front.
Your team starts from the analytical work it already did, then curates what matters.
Faster analyst onboarding.
New analysts can inspect validated business logic instead of reverse-engineering tribal knowledge.
Knowledge survives departures.
Definitions live in the Context Graph, not only in notebooks, dashboards, or someone's memory.
The moat is customer-specific.
Your Context Graph is built from your assets and usage. It compounds inside your environment.
Continue the Frame