TableAI makes any table in your product answer questions
Embed conversational answers directly into the tables and reports your users already rely on. No data migration. No new reporting workflow. Just better answers inside the product.
Built for products where tables are already part of the workflow
Embedded in the report
Users stay inside the table or dashboard they already understand.
Natural-language questions
Users ask what they want in plain language instead of learning filters and export workflows.
Answer plus chart
Return a direct answer and the right visual when the question needs more than a sentence.
No data migration
Keep the tables, pipelines, and product model you already have in place.
Privacy-aware answer modes
Choose full AI, masked, hybrid, or local execution based on the account's requirements.
Usage and access controls
Control who can query, how often, and which customers get access to the feature.
How TableAI works inside your product
Start with the tables your users already know
Static reporting already exists in your product. TableAI turns that existing surface into a place where users can ask for answers instead of opening tickets.
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No new reporting destination for users to learn.
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No new data pipeline required just to launch the experience.
Provide report, user, and tenant context
TableAI uses the current report state, filters, account, and user context so the answer fits the existing product model instead of becoming a disconnected chat widget.
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Keep answers aligned with the permissions and scope users already have.
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Stay consistent with the way the product already thinks about data.
Choose the privacy posture per customer account
Not every customer wants the same answer path. TableAI lets you choose the right mode, from full AI to masked, hybrid, or fully local execution.
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Balance answer quality with governance requirements.
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Support enterprise accounts without forking the product strategy.
Turn analytics into a stronger product capability
TableAI reduces ticket dependency, increases report usage, and creates a new surface you can monetize or package by customer tier.
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Give customers self-serve answers inside the workflow.
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Control access and query volume to protect cost and value.
Why teams embed TableAI
Tables become answer surfaces
Users ask instead of guessing which filter, export, or ticket they need next.
Fewer support tickets
Routine report questions get answered inside the product instead of being pushed to support or customer success.
Faster time to launch
Ship an AI-smart reporting experience without rebuilding your analytics stack from scratch.
Better enterprise fit
Support different privacy expectations without splitting into separate product lines.
New monetization route
Turn AI query access into a product control by account, tier, or user profile.
No rebuild required
Keep the product architecture you have and add intelligence at the table layer.
FAQs on TableAI
What is TableAI?
TableAI is Teptro's embedded AI product that lets users ask questions of the tables and reports already present in a B2B product.
Do we need to migrate our data to use it?
No. TableAI is designed to work with the reporting surfaces you already expose, rather than requiring a new warehouse or reporting workflow.
Can users ask natural-language questions?
Yes. Users can ask the next question they actually have in plain language, and TableAI returns an answer plus a chart when the context calls for it.
How do the privacy modes work?
TableAI supports multiple answer modes, including full AI, masked, hybrid, and local execution, so teams can choose the right tradeoff per customer profile.
Can we control who gets access to TableAI?
Yes. Query access and usage can be controlled by customer, tier, or user depending on the product strategy you want to run.
Who is TableAI built for?
It is built for B2B products that already rely on tables and reports in the workflow and want to make those surfaces more intelligent without rebuilding the stack.