AI to analyze your company's data

Why pasting data into a chat doesn't work

Pasting a spreadsheet into a generic chatbot works for a one-off analysis — but it doesn't scale and it creates risk: the data leaves the controlled environment, the answer isn't reproducible and nobody audits what was sent. For AI to truly analyze data, it needs governed access to an organized foundation.

What you can ask

• "Which product had the biggest margin drop this month?"
• "Why did revenue fall in the Southeast region?"
• "Which customers are at the highest risk of revenue decline?"
• "Create an executive report on this week's sales."

How it works under the hood

The AI knows your data model (tables, measures, business rules), converts the question into a query, runs it on your datalake with a cost cap and returns the answer with the right chart. The AI model processes the question, the schema (without columns tagged as sensitive) and the results it needs — not your entire database. For maximum isolation, there's a bring-your-own-cloud option (BYOC).

Beyond the question: reports and monitoring

The AI Analyst (from the Growth plan up) schedules executive reports, generates insights on dashboards and watches KPIs — flagging anomalies and projecting trends, with a PDF attachment from Business up. It's the difference between an AI that answers and one that works for the team on a recurring basis.

How ingestia.io helps

ingestia.io brings AI built into the data platform: ask in natural language, get analyses on the cleaned foundation and schedule AI Analyst reports. Asking your data is in every plan (the AI Analyst from Growth up), with metered AI usage, a monthly cap per workspace and per-query cost limits — you can try it without an extra contract and without surprises on the bill.