/ solutions / data & it
TextQL for Data & IT Own the Layer, Not the Queue
Every team asks Ana in the tools it already uses. Every answer comes from one layer your team owns — defined once, as code, in your repo.
An AI-Powered Operating System for Data & IT
Put the semantic layer, internal tools and governance on one ontology your team owns — and let every team ask it directly, under the permissions you already set.
Connected solutions + automations
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- Metric definitions
- Business context
- Reviewed in Git
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- Ops consoles
- Approval queues
- Write-back to source
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- Ontology health checks
- Row-level access
- Lineage to source
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- Your cloud or air-gapped
- Model-agnostic
- Yours to export
The Projects Data Teams Start With
Four transformations, each with a page of its own and a first engagement scoped to it. Start with the one costing your team the most today.
- 01 / BI Consolidation Stop Renting Your Dashboards Fixed scope: a set number of dashboards, a set number of weeks. first engagement · Assess a BI migration
- 02 / Conversational Analytics Ask Anything. Trust Every Answer. Starts on the warehouse you already have. Nothing moved, no new BI tool. first engagement · See it on your warehouse
- 03 / Data Warehouse Migration Get the Answers Before the Migration Finishes Start with the systems you already run. Nothing has to move first. first engagement · Map a migration
- 04 / Own Your Ontology Own the Ontology That Runs Your Business Model-agnostic, in your cloud, with your permissions intact. first engagement · Book a demo
Watch the story“With TextQL, our analysts can now focus on high leverage tasks and the most challenging problems.”
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TextQL empowers Scale AI to answer ~1,900 data requests per week across four business units, all governed through one semantic layer.
- of Scale’s dbt code reviewed by Ana
- >50%
- rows across tables handled in production
- 1.9T
- organic monthly adoption
- +74.9%
Bring the Request Your Team Gets Every Week
Pick one — the metric two dashboards disagree on, the report someone rebuilds every Monday, the question stuck in the queue. We connect inside your cloud and show your team the answer, the SQL and the definition behind it.
- 01 Pick the request A 30-minute call to choose the request and the sources behind it
- 02 Connect in your cloud We connect inside your cloud — your data is read in place, never copied out
- 03 Check the SQL Your team reviews the answer, the SQL and the definition before anyone else sees it
- Why do Tableau and Looker disagree on revenue? Ontology & Semantic Layer
- Can ops get a refunds queue by Friday? Internal Tools & Data Apps
- Which metrics read a table that failed last night? Data Quality & Governance
- Can EU customer data stay in the EU region? Sovereign Ontology
- Which of our dashboards does anyone still open? BI Consolidation
- Can sales ask for pipeline in Slack and see only their region? Conversational Analytics
- Can we change warehouses without the numbers moving? Data Warehouse Migration
- What would it take to own the ontology we rent today? Own Your Ontology
The Platform, in Your Team’s Terms
Three layers, one deployment. Each is a page of its own when you want the detail.
Built to Pass Your Security Review
No. TextQL reads the models and definitions you already have and keeps the ontology beside them, as reviewed files in your own repository. Your team decides what each metric means; every tool reads that one.