AI Analytics: read what your data is actually saying
I connect your data sources, build models that find patterns you cannot spot manually, and give you dashboards you can act on. You stop guessing and start deciding.
What the data looks like once it can talk back
These are examples of dashboards and models I build. Your numbers will look different; the clarity is the same.
Revenue Prediction
AI predicts 24% growth based on current trends
Customer Segmentation
32% of customers, 67% of revenue
Live Business Metrics
What I build for you
Three things I do most often, with clients across e-commerce, services, and early-stage startups.
Predictive Analytics
I build models that forecast revenue, predict which customers are about to leave, and estimate demand before it happens, so you have a number to plan around.
- Revenue forecasting
- Customer churn prediction
- Demand forecasting
- Market trend analysis
Real-time Dashboards
Dashboards your team can open every day, not every quarter. I connect live data sources and set alerts so the right person knows when something needs attention.
- Live KPI monitoring
- Custom visualizations
- Automated reporting
- Mobile-responsive design
Customer Intelligence
I segment your customers by actual behavior, calculate lifetime value, and map the journey so you know where people drop off and why.
- Behavioral analysis
- Customer journey mapping
- Lifetime value calculation
- Personalization insights
Two clients, before and after
Specific problems, specific numbers, specific timelines.
TechHub Electronics
Challenge: Online electronics retailer struggling with inventory management and customer churn, losing $500K annually due to stockouts and 35% customer attrition.
My Solution: Implemented AI-powered demand forecasting, customer churn prediction models, and real-time inventory optimization dashboards.
SecureFinance Solutions
Challenge: Financial services company needed better fraud detection and risk assessment, experiencing $2M in annual fraud losses and slow loan approvals.
My Solution: Built AI-powered fraud detection system, automated risk scoring models, and real-time transaction monitoring with anomaly detection.
How I work
Four steps, in order. Nothing is skipped; each one builds on the last.
Data integration and preparation
I connect your existing sources (GA4, ad platforms, CRM, databases) and clean the data so the models have something reliable to work with.
Deliverables
- APIs & ETL
- Data Cleaning
- Cloud Storage
- Real-time Sync
Model development
I train models on your specific data. Forecasting, churn prediction, segmentation: the model depends on the question you actually need answered.
Deliverables
- Machine Learning
- Deep Learning
- Model Training
- Validation Testing
Dashboards and reports
The model output becomes a dashboard your team can open every morning. I write plain explanations alongside the charts, not just numbers.
Deliverables
- Data Visualization
- Interactive Dashboards
- Automated Reports
- Alert Systems
Ongoing refinement
Data changes. I monitor model performance, retrain when the numbers drift, and add new questions as your business grows.
Deliverables
- Performance Monitoring
- Model Retraining
- A/B Testing
- ROI Tracking
Estimate what better data decisions are worth
The calculator below is a rough guide, not a guarantee. I am happy to work through a more honest estimate together once I know your setup.
Most clients go from weekly spreadsheet exports to same-day dashboards.
Not perfect, but far better than gut feel or manual trend lines.
Hours your team spends pulling and cleaning reports get redirected to decisions.
ROI Estimator
Want to know what your data is actually telling you?
Tell me what you are working with and what you wish you could see. I will show you whether AI analytics is the right tool and what I would actually build.
Tell me about your setup
No commitment required. See AI analytics in action with your own data.