Business Analytics AI
We deploy an assistant that turns your existing data sources into plain-language KPI analysis, trend reports, and forecasts, supporting faster reporting, clearer executive dashboards, and better-informed decisions.
An AI assistant that connects your dashboards, spreadsheets, and databases so teams can ask questions in plain language.
What an engagement can include
We confirm the final deliverables after reviewing your goals, current setup, dependencies, and priorities.
- A KPI reporting layer that summarises agreed metrics from your connected sources and answers questions in plain language
- Sales analysis views that break performance down by product, channel, region, or period on request
- Trend detection that surfaces meaningful movements and anomalies across your key measures
- Forecasting that projects selected metrics forward with the assumptions and ranges stated clearly
- A natural-language query interface configured against your dashboards, spreadsheets, and databases
Process
How we deliver business analytics ai
The exact sequence is adjusted to the scope, but responsibilities and review points are agreed before delivery begins.
- 01
Discover
Identify the metrics, questions, and reports that matter, then map the data sources and access needed to answer them reliably.
- 02
Connect
Integrate the assistant with your dashboards, spreadsheets, and databases, and define how each metric is calculated.
- 03
Configure
Tune the natural-language queries, KPI definitions, trend rules, and forecast assumptions against real questions from your team.
- 04
Launch
Roll out the assistant to agreed users, review answer quality, and refine definitions and dashboards from actual usage.
Tools
Tools selected for the work
We choose tools based on the project requirements, your existing systems, and the needs of the people who will maintain the work.
- OpenAI
- BigQuery
- Metabase
- Looker Studio
- GA4
FAQ
Questions about business analytics ai
It works from the data sources you connect, such as dashboards, spreadsheets, and databases. It does not invent figures; answers reflect the metrics and definitions configured during setup, so accuracy depends on the quality and freshness of the connected data.
It can project selected metrics forward based on historical patterns and stated assumptions, and it presents ranges rather than single certainties. Forecasts are decision-support estimates that should be read alongside business context, not guarantees of future results.
Pair with
Related capabilities
Depending on your goals, business analytics ai may also benefit from:
- View service
Search Engine Optimization
Technical and content SEO that compounds month over month.
- View service
Sales & Lead Qualification AI
An AI assistant that engages prospects, qualifies leads, follows up automatically, and books meetings with your sales team.
- View service
Meeting & Executive AI
An AI assistant that records, summarises, and organises meetings so teams focus on execution instead of note-taking.
Planning a business analytics ai project?
Share your goals, current setup, and constraints. We will help you define a practical scope and next step.