The agentic analyst for your business
Ask in plain English. Get an approved answer. Reuse it every time.
Spotonix answers business questions using the definitions your team already follows — and shows the plan behind every answer.
> Which stores are losing habitual buyers this quarter?
Which do you mean?
✓Habitual Buyers saved
The plan, before the query runs
12 stores losing habitual buyers
> Top categories habitual buyers shop this year?
Reused from your approved definitions
5 categories — Men leads at $18.3K
Three business outcomes
Your data isn’t the bottleneck.
The queue in front of it is.
SPEED
30–60seconds
Not the days it takes to get through the analyst queue.
Ask recurring business questions directly, without opening another ticket or building another dashboard.
CAPACITY
40–70%
of analyst time Spotonix is built to give back.
That’s how much of an analyst’s week goes to ad-hoc requests today. Analysts review the plan instead of rebuilding the query.
TRUST
Same plan.
Same query.
One accepted logic, not five versions of the number.
Reuse the logic your team accepted across teams and reporting cycles, with the plan always available to inspect.
Internal Spotonix benchmark, July 2026 · median time to a reviewable answer, against comparable systems at 4–7 minutes on the same question set and environment · results vary by question complexity. Analyst-time finding from customer-discovery interviews at design-partner organizations.
Common question
“Can’t Claude or ChatGPT
just write the SQL?”
Claude and ChatGPT can generate a plausible query, but a plausible query is not an approved answer. Ask a general model this question:
> Are we losing habitual buyers in the Northeast?
WHAT A GENERAL MODEL IMPROVISES
- What counts as habitual?
- Does “losing” mean fewer visits, lower spend, or churn?
- Compare to last quarter, prior year, or a trailing average?
- What decline is material?
- Tie customers to which store?
Inferred from the prompt and liable to vary across runs — with no durable record of why.
WHAT SPOTONIX RESOLVES
- ✓ Cohort → your approved habitual-buyer definition
- ✓ Metric → your store-purchase-frequency measure
- ✓ Comparison → current quarter vs prior-year baseline
- ✓ Threshold → below the level your team has accepted
- ✓ Scope → your Northeast geography
Resolved against the definitions you already approved. Shown before any query runs. Ambiguous terms trigger clarification; the accepted meaning can then be saved for reuse.
Spotonix supports model providers and runtimes including Anthropic, OpenAI, Amazon Bedrock, Google Vertex AI, and private inference. The model proposes an interpretation; Spotonix maps it to your approved definitions, shows the plan before the query runs, and saves the accepted logic for reuse. Better models make Spotonix better, not obsolete.
For the whole company
Turn one answer into
a repeatable business review.
Use an accepted answer to review what changed, prepare the brief, and record the decision — a repeatable workflow that keeps context across reviews.
01
Review what changed.
Re-run an accepted question and compare the latest result using the same approved definitions.
02
Prepare the brief.
Share the result, the accepted plan behind it, and a link to the answer — before the meeting.
03
Record the decision.
Capture the team’s decision alongside the answer, so the next review starts with the same context.
How it works
Ask. Review. Reuse.
Three steps. The first two are how you work with Spotonix; the third is why the second question is easier than the first.
01
Ask in your business language.
Spotonix reads your warehouse, semantic models, and approved query history — so you ask in the words your team already uses, not column names.
02
Review the plan before it runs.
See the definitions and assumptions behind the answer — metrics, filters, grain, joins. If several meanings fit, Spotonix asks instead of guessing.
03
Accept it once, reuse it after.
Once your team accepts the plan, Spotonix saves it with its query logic and can reuse it for later questions and recurring reviews.
Same accepted plan. Same query. Every time.
Proof
Built for private data.
Deployed with design partners.
Deploys in your VPC or cloud boundary where required · bring your own model key · self-host option · queries execute as the logged-in user, so warehouse and BI-layer permissions are enforced at query time.
“Spotonix is taking a first-principles approach to building business context. This is essential for the coming world of agentic data applications.”
“The context layer is the missing piece in modern data stacks.”
“Most analytics tools optimize for speed. Spotonix optimizes for institutional memory. That’s an entirely different game.”
Works with
Deployed with design partners in AdTech, FinTech, and PaaS. Built for teams with governed warehouses, existing BI setups, and approved business definitions.
Backed by
and by the founding team of Looker
Team
Built by founders with
a long history in BI and query engines.
Venkatesh Seetharam
Co-founder & CEO
Co-creator of Apache Atlas, creator of Apache Falcon. Built data-platform teams at Hortonworks and Yahoo!. Investor at 8VC.
Harish Butani
Co-founder & CTO
Built four BI engines including OLAP on Spark (SparklineData, acquired by Oracle). Co-creator of Apache Atlas. Contributor to Oracle, SAP HANA, Apache Hive.
Bob Muglia
Advisor
Former CEO of Snowflake and former President of Microsoft's Server & Tools Business.
A practical first step
Prove the value on
your own data.
Start with one high-friction question workflow. Before setup, agree on the current baseline and what success looks like. Then measure Spotonix against the way your team works today.
01
Time to an approved answer.
Compare how long the same business question takes before and during the proof.
02
Analyst review and rework.
Track how much analyst involvement is needed to reach an accepted result.
03
Answer consistency.
Repeat agreed questions and verify that the same accepted logic produces the same query.
A two-week proof on your data. No commitment. Expand only if the results make the case.
Prove an approved-answer workflow
on your data.
Start with a two-week proof on your data — no commitment. Or talk to us first.