Transformations / conversational analytics
Ask Anything. Trust Every Answer.
Your data stays where it is. Anyone can ask in plain English — and every answer stays live and shows each person only what they’re allowed to see.
AI on Your Data, Before and After
- AI answers pulled into files, then forwarded anywhere
- Whoever gets the file sees every row in it
- Each chat decides what revenue means
- A chart that was right on Monday, wrong by Friday
- Ask from Slack, Teams or your AI assistant — data never moves
- Every answer filtered by who is asking
- Every metric read from one governed definition
- Every query logged, every number traceable
Everyone Asks. Everyone Sees Only Theirs.
The same question means different answers for different people — and it should. Every answer runs under the access rules in your ontology, so sales in EMEA sees EMEA, finance sees everything, and a contractor sees nothing they shouldn’t.
- Row- and column-level rules defined once, in your repository
- Enforced on every question, from every surface people ask from
- Every answer logged with who asked and what they could see
- amer
- emea New logos $3.1M
- apac
- emea Enterprise renewals $4.2M
- amer
- apac
Answers That Stay True
An answer pasted into a doc is a picture of the data on the day it was drawn. Ask TextQL and the answer is a dashboard: it re-queries on schedule, so the number people act on is today’s, not last Monday’s.
- Any answer saved as a dashboard with one click
- Refreshed on the schedule you set, in your own cloud
- The questions asked every Monday answered every Monday
Chat export bookings.html- client
- profile
- software services · charlotte, nc
- file
- snowflake → ana, in slack
- status
- live · default analytics layer
Every executive asks Ana first.
Every new executive spends their first two weeks talking to Ana. They get going without using our data resources — they just ask her questions in Slack and get detailed feedback about what’s happening.
Three Steps, on the Warehouse You Already Connected
No new BI tool and no migration project. The same warehouse, the same questions — answered in a form that lasts.
- 01 / connect Read What’s There Point TextQL at the warehouse your AI already queries. It reads the schema, the joins and the metrics people keep asking about. no data copied
- 02 / define Agree the Numbers The metrics everyone asks for are defined once, in your repository, and signed off by the people who own them. one definition each
- 03 / ask Answers That Last People keep asking in plain English — in Slack, Teams or their AI assistant. What comes back refreshes, shares safely and is logged. live, governed
See It on Your Warehouse
Bring the questions your team already asks AI. We connect to the warehouse you use, define the metrics behind them, and turn the answers into dashboards you own.
- 01A 30-minute call to pick the questions and the warehouse
- 02We define the metrics behind them, inside your cloud
- 03Your team asks away — and every answer stays live
Where It Starts
- 01 AI on Snowflake, governed
Keep the AI your team already uses on the warehouse, and make what it produces refresh and respect access.
- 02 Retire the HTML dashboards
Find the AI-made dashboards people actually reuse and turn them into live ones; let the one-offs go.
- 03 Ask from Slack and Teams
Plain-English questions where people already work, answered from the same governed definitions.
- 04 Board-ready numbers
Every figure traced to its query and definition, so the number in a chat is the one finance signs off.
- 05 Scheduled answers
The questions people ask every Monday, answered every Monday — as playbooks, not a pasted chart.
- 06 Row-level security by default
Every answer inherits the warehouse’s own permissions, so a forwarded dashboard never shows more than it should.
Keep it. The gap is what happens after the answer: a static file that doesn’t refresh, doesn’t carry your permissions and defines revenue however that chat decided to. TextQL makes the answer live, governed and consistent.