A scoring model trained on your data, not a generic API call.
Lead scoring, churn prediction, demand forecasting, built on your historical data, validated against your business KPIs, and deployed into your existing stack.
Six capabilities your model brings out of the box.
Trained on your data
Not a fine-tuned generic model, a model built for your schema, your labels, and your business logic.
Classification & scoring
Lead quality, customer risk, document type, transaction category, any classification problem your team currently does by hand.
Forecasting
Demand, churn, revenue, and inventory, at whatever horizon makes the most business sense.
API deployment
A single REST endpoint your team can call from any tool, pipeline, or dashboard. No ML knowledge required to use it.
Explainability
Feature importance reports so every decision can be audited, explained, and challenged by a human.
Drift monitoring
Automatic alerts when model performance starts degrading, before bad predictions reach your team.
From raw data to a live prediction API in 14 days.
Data audit
We map your historical data, identify quality issues, and define the target variable before writing a line of model code.
Feature engineering
We extract and transform the predictors that are actually relevant to your business outcome, not just whatever is in the schema.
Train & validate
Model trained on historical data, validated on a held-out test set. You approve the accuracy threshold before deployment.
Deploy & monitor
REST API on your infrastructure or managed cloud. Drift detection and scheduled retraining included.
Three models. Three measurable deltas.
Every model below started as a spreadsheet or a gut-feel decision. Now it runs automatically.
ZENITH INSURANCE
AI claims triage and document extraction pipeline. Standard claims extracted, scored, and settled automatically, specialists only handle the cases that genuinely need them.
VELOPORT
Gradient boosting model forecasts weekly SKU demand from 3 years of sales history, seasonal signals, and external event data, replacing a manual Excel process.
CREDEX FINANCE
Churn scoring model flags at-risk accounts 45 days before cancellation and triggers automated retention sequences, before the customer picks up the phone.
Questions we get on every call.
How much data do I need?
It depends on the task. Classification often works with a few hundred labelled examples. Forecasting needs at least 12 months of history with consistent structure. We will tell you in the first call if your data is not ready yet.
Can you connect to our internal data warehouse?
Yes. We connect to BigQuery, Snowflake, Redshift, Postgres, or flat files, wherever your data lives.
What if the model is not accurate enough?
The SOW includes a validation accuracy threshold. If we do not hit it, we keep iterating until we do, within the agreed scope.
Who owns the model?
You do. All weights, training code, and data pipelines are transferred to you at handoff. No vendor lock.
Replace gut feel
with a model.
30-minute call. We'll audit your data and tell you exactly what is and isn't ready for a custom ML model, free, no deck.
Coming soon.
Our Back-Office AI systems are in final testing. Explore our Customer-Facing AI, in production now and deploying in 14 days.