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What Product Categories do High Spenders like to shop?
"High spenders" matches two Segments. Pick one — or rephrase.
✓ "Spend > $5,000 / year" validated and added to your Context Graph
Analyst · How it works
The Analyst learns your context, composes a plan before SQL, and compounds every accepted answer. The same Context Graph later powers the Advisor.
You Ask, Review, and Reuse. Underneath, Spotonix Learns, Composes, and Compounds. This page is the underneath.
Every verified answer starts from learned business context, not a blank prompt.
LEARNS / 01 · Builds the Context Graph
Schema, your modeling layer, BI assets, and approved query history. Spotonix studies the corpus and constructs a Context Graph — yours alone.
Your Context Graph · TPC-DS retail
If intent is ambiguous, it asks. If definitions conflict, it refuses to guess. Same accepted plan. Same SQL. Every time.
COMPOSES / 02 · Clarifies ambiguity
First time Spotonix sees an ambiguous term, it asks you to clarify or rephrase. Every subsequent question uses your validated definition automatically — no re-asking. The clarification is a one-time tax — once accepted, that decision becomes reusable context for every future plan.
"High spenders" matches two Segments. Pick one — or rephrase.
Plan · auto-applied from Context Graph
Clarifies once. Reuses every time. Every disambiguation strengthens the Context Graph — and shortens the next question.
COMPOSES / 03 · Shows the plan
A real, multi-concept question. Every interpretation is a graph — named nodes, named edges — that you can read in seconds. The composed plan is the trust surface — SQL only compiles after the intent is closed.
COMPOSES / 04 · Binds governed definitions
“Sales” living in three tables under three names is the easy part. The hard part: sales isn’t revenue, gross isn’t net, and a unit price was never meant to be summed. An prompt-only tool conflates them and answers — confidently. Spotonix binds every metric to its real definition — family, variant, gross-vs-net, channel, additivity — and when the binding would be wrong or ambiguous, it refuses or asks instead of guessing.
COMPOSES / 05 · Composes exploration paths
Sometimes the right question is "show me what's interesting." Spotonix proposes four candidate Segmentations — each with its own Intent Algebra — and lets you drill into any of them.
Three customer-related dimensions surfaced from your Context Graph — all joined to store_sales, catalog_sales, web_sales. Each attribute below is an axis you can segment on; no values fetched yet.
Dimension
customeridentity & lifecycle
c_preferred_cust_flag 2 values flag_partition c_birth_year date cohort_window c_first_sales_date_sk date cohort_window Dimension
customer_demographicsdemographic profile
cd_gender 2 values cross_segment cd_marital_status 5 values cross_segment cd_education_status 6 values cross_segment cd_credit_rating 4 values cross_segment Dimension
customer_addressgeographic · hierarchical
ca_state 50+ values dimension_drilldown ca_city many dimension_drilldown ca_zip many dimension_drilldown COMPOUNDS / 06 · Reuses accepted plans
Watch five real questions play through. The Segments and Calculations from each Answer persist — and the reuse rate climbs as the graph fills in. The 100th question starts with more accepted context than the 1st — most of its building blocks already exist.
Three Ways to Experience It
Start with the hosted demo, then bring your own artifacts into a guided evaluation.
Fastest · in seconds
A working Spotonix instance against a sample retail dataset. Verify your work email, then sign in with Google.
Request sandbox access →Most Relevant · use your own model
See how Spotonix interprets your own DAX models — dry-run, no warehouse credentials required.
Coming soon · talk to founders for early access →Deepest · founder-led
Bring your questions, data challenges, or PBIX files into a founder-led session tailored to your business.
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