AI Business Analytics & Reporting

Ask a question in plain English — "what drove last month's revenue drop?" — and get a direct answer, not a blank query editor.

The AI Employee watches your key metrics continuously and flags unusual spikes, drops, or trends the moment they happen — no manual dashboard-checking.

Dashboards and reports rebuild themselves as new data lands, so what you're looking at is never stale.

Connects natively to your data warehouse, spreadsheets, and BI tools, so it works with the data stack you already have.

A written summary of what moved and why, delivered on your schedule to email or Slack, so the numbers reach the people who never open a dashboard.

Each answer arrives with the query it ran and the records it used, so you can check the number before you act on it.

Data analysts and scientists spend an estimated 50-80% of their time collecting, cleaning, and preparing data before any actual analysis can begin.

Forrester research found that 60% to 73% of all data within an enterprise goes unused for analytics, sitting idle instead of informing decisions.

A logistics company's AI data agent cut manual reporting time by 90%, saving roughly $420,000 a year that previously went to 20+ hours a week of manual data pulls across five systems.

British Columbia Investment Management Corporation saved 2,300 hours and saw a 10-20% productivity gain for 84% of users after deploying AI-assisted analytics.

McKinsey Global Institute found data-driven organisations are 23 times more likely to acquire customers, six times as likely to retain them and 19 times as likely to be profitable.

In NewVantage Partners’ survey of large enterprises, just 24% described their organisation as data-driven — despite near-universal spending on data initiatives.