AI solutions
AI analytics
Natural language querying over a governed semantic layer, plus model-driven forecasting and anomaly detection. Answers cite the underlying rows, because a number nobody can trace is not an insight.
What is included
- Natural language to SQL over a governed schema
- Forecasting for demand, revenue and churn
- Anomaly detection with alerting
- Row-level provenance for every generated figure
How we would start
Discovery
Two weeks with the people who will use the system. We interview them, map the process, and write down what exists and what is missing.
Written scope
Requirements, acceptance criteria and explicit exclusions. A number attached, so you can compare it against other options.
Build and ship
A dedicated pod, weekly working software, and a demo of something real every sprint rather than a status report.
Operate and improve
Monitoring, maintenance and a monthly conversation about what to change next. We stay on the system we built.
Questions
What clients ask about AI analytics
The questions that come up before this kind of project starts. The same answers are published as structured data, so search and answer engines can quote them.
How does asking questions of our data in plain language work?
Your question is translated into SQL against a governed semantic layer, so the model can only query what it is allowed to see, and every answer cites the underlying rows.
Can you forecast demand, revenue and churn?
Yes. We build forecasts with backtesting against your own history, so you can see how the model would have performed before you rely on it for a decision.
Do you alert on anomalies?
Yes, with thresholds agreed with the people who will act on the alert. An alert that nobody acts on is noise, so we tune for precision before switching it on.
Let's build together
Tell us what you are building. We will tell you honestly whether we are the right team for it.
Send a paragraph about the problem. You will get a reply from an engineer, not a form letter, within one business day. If we are not the right fit, we will usually know someone who is.
What happens next
- 1 We reply with initial questions, a rough range and whether we are the right fit.
- 2 A call or a workshop with the engineers who would actually do the work.
- 3 A paid discovery phase produces a written scope and a number we can stand behind.