A2 — AI Apps & Integration
AI-Powered Analytics & Predictive Modeling
Forecasts, anomaly alerts and decision support built from your business data with machine learning models.
Overview
Most businesses already have the data to see problems and opportunities earlier. The difficulty is turning it into forecasts and alerts people trust and act on.
We start from the decisions you want to make, prepare your data, build and validate predictive models, and deliver the results where your team already works.
What we do
- 01
Assess your data and the decisions it should support
- 02
Clean and prepare data for modelling
- 03
Build forecasting and anomaly-detection models
- 04
Validate model accuracy on held-back data
- 05
Deliver results in dashboards or alerts
How we work
- Step 1
Discover
We agree the use case, data sources and what a good answer looks like.
- Step 2
Build
We integrate the model, your data and your product in short iterations.
- Step 3
Evaluate
QA tests accuracy, safety and edge cases against an evaluation set before launch.
- Step 4
Monitor
We track quality and cost in production and keep improving.
Who it's for
- Teams making decisions on gut feel despite having data
- Businesses wanting early warning of unusual activity
- Companies planning stock, demand or staffing
What you get
- A data and use-case assessment
- Validated forecasting or anomaly models
- Dashboards or alerts for your team
- Documentation of how the models work and their limits
Questions
How much data do we need?+
It depends on the problem. We assess your data first and tell you honestly whether it's enough before building anything.
How do we know the predictions are reliable?+
Models are tested on data they haven't seen, and we report their accuracy and limits in plain language.
How quickly can you start?+
Most engagements start within 5–7 business days of agreeing scope, and urgent work can start within 48 hours.
Tools
- Python
- OpenAI
- AWS Bedrock
- Looker Studio
- GA4
