Predictive analytics services.
See next quarter, this quarter.
Forecasts and risk scores built into dashboards and workflows leadership already uses.
The problems we solve first.
Spreadsheet forecasts
Plans built on last year plus a guess.
Too many dashboards
Insight lost in reports nobody opens.
Trust
Leaders ignore numbers they cannot explain.
What you get.
Every engagement includes design, engineering, evaluation, security review and handover from one senior team.
Forecast models
Sales, demand and cash flow.
Risk scores
Churn, default and fraud risk.
Scenario tools
What-if planning.
Dashboards
Predictions in BI tools.
Alerts
Notifications when numbers move.
Accuracy tracking
Forecast versus actual.
Predictive analytics, by industry.
How we ship AI that holds up.
Evaluation comes before scale. You see it working on your data before you commit to the full build.
Discover
Pick the task, define what “good” means and collect sample data.
Prototype
A working version on your real data, shown to real users.
Evaluate
Automated tests for accuracy, latency, cost and safety.
Productionise
Security, scaling, integrations and admin controls.
Monitor
Quality, drift and spend tracked; prompts and models improved.
Three ways to start.
AI sprint
One use case, prototyped on your data and tested with users.
You leave with · Prototype + go/no-goPilot
A production-grade version for one team, with evals and monitoring.
You leave with · Live pilot + ROI dataAI team
A dedicated squad that ships and improves AI across your products.
You leave with · Roadmap deliveredQuestions, answered.
Most clients start with a two-week AI sprint. Pilots and production builds are priced after the sprint, once we know what works on your data.
Ready to try predictive analytics? Start with a sprint.
Tell us the task. An AI architect replies within one business day with a sprint plan. NDA on request.