See demand coming. Keep customers before they leave.
I build predictive models on your business data — who is likely to churn, what demand is coming, which cases carry risk. Every model is validated on data it has never seen, explained in plain language, and delivered as an API or dashboard your team actually uses.
Decisions that stop being guesswork
01Customers leave without warning
Churn is usually visible in the data weeks before it happens. A churn model scores every customer by risk, so your team can act while there is still time to keep them.
02Inventory planned by gut feel
Too much stock ties up cash; too little loses sales. Demand forecasting turns your sales history into per-product forecasts your purchasing can plan around.
03Risk judged inconsistently
Credit, order and case decisions vary by person and by day. A risk score ranks every case the same way, so human review goes where it matters most.
04Years of data, zero predictions
Your CRM and sales history already contain the patterns. The work is cleaning that data, training the right model, and proving it beats the simple baseline.
What you receive
✓Churn prediction model
Every customer scored by churn risk, with the main reasons behind each score — not just a number.
✓Demand forecasting
Product- and location-level forecasts with accuracy measured honestly against your own history.
✓Risk scoring
Consistent scores that rank applications, orders or cases for human review.
✓Explainable outputs
SHAP-based explanations show which factors drive each prediction, so your team can trust — and challenge — the model.
✓API or dashboard delivery
Predictions served through a FastAPI endpoint or a simple Streamlit dashboard your team opens every day.
✓Validation report
Held-out performance, the baseline it beat, known limitations, and what data would improve it next.
Tools & technologies
Python & pandas
Data cleaning and feature engineering — where most of a model's real quality is decided.
XGBoost
Gradient-boosted models that handle messy, real-world business data reliably.
scikit-learn
Baselines, training pipelines and rigorous evaluation.
SHAP
Per-prediction explanations your team can read and act on.
FastAPI
Fast, documented APIs that serve predictions to your existing systems.
Streamlit & PostgreSQL
Dashboards for daily use, backed by a proper database.
From raw data to working predictions
Data audit
We look at what you actually have: volume, quality, history. If the data cannot support a reliable model, I will tell you before you spend anything.
Baseline first
A simple baseline sets the bar. The model only ships if it clearly beats doing things the obvious way.
Build & validate
Training on historical data, testing on held-out data the model never saw. Accuracy, errors and blind spots documented.
Deploy & hand over
API or dashboard live, documentation delivered, and a clear path for retraining as new data arrives.
Straight answers
A custom prediction model starts at $1,490, with the exact scope and price fixed in writing before work begins. A data audit first confirms the project is worth doing at all.
As a rule of thumb, several months to a few years of customer or transaction history. What matters most is that outcomes are recorded — who churned, what sold, when. The data audit answers this for your specific case.
Accuracy is measured on held-out data the model never trained on, and reported next to a simple baseline. I will never promise a number before seeing your data — anyone who does is guessing.
Through an API your systems call, a dashboard they open, or scheduled scores and alerts. We choose whatever fits how your team already works.
A focused model typically takes two to four weeks from data access to deployed predictions, depending on data quality and the number of prediction targets.
Related services
AI & Machine Learning Engineering →
The model-building craft behind these services — custom models, computer vision and NLP.
Dashboards & Business Intelligence →
Put predictions on one screen your team checks every day.
API Development & Integrations →
Serve predictions to your existing software through a clean, documented API.
Let's find out what your data already knows
Book a free 30-minute call. Bring your questions about churn, demand or risk — I will tell you honestly whether a model will help, and what it would take.
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