ML models that score, forecast, and classify: in production, not notebooks
Prediction systems that run 24/7. Not proof-of-concepts gathering dust.
We build machine learning models for the decisions that move your business: demand forecasting, risk scoring, churn prediction, pricing optimization. Every model ships with monitoring, retraining pipelines, and integration into the workflow where the decision actually happens.
What We Build
Predictive Models
Forecasting, scoring, classification: models trained on your data, deployed where the decision happens.
Anomaly Detection
Fraud, outliers, drift: catch what humans miss at millisecond latency. Production-grade, not notebook experiments.
Time-Series Forecasting
Demand, staffing, pricing: predict what happens next with models that account for seasonality and trends.
NLP & Text Analytics
Sentiment, extraction, classification: turn unstructured text into structured insights your systems can act on.
Recommendation Engines
Personalization at scale: product, content, and next-best-action recommendations that compound engagement and revenue.
Model Ops
Training pipelines, retraining, monitoring: models that stay accurate as data shifts. Automated, versioned, auditable.
How It Works
Data Audit
Assess data quality, availability, and gaps. Define the prediction target and success metrics before writing a line of code.
Model Development
Feature engineering, model selection, training, and validation. Iterative experimentation with rigorous evaluation.
Production Deployment
Deploy models with monitoring, retraining pipelines, and integration into the decision workflow where results matter.
Where We Apply This
Banking & FinTech
Banks and fintechs need AI that scores risk in milliseconds, catches fraud without blocking good customers, and meets regulatory requirements without a 12-month compliance project. We build those systems.
View industry →E-commerce & D2C
E-commerce at scale is a data problem disguised as a retail problem. We build recommendation engines, demand forecasting models, dynamic pricing systems, and commerce platforms that turn browsing into buying.
View industry →Manufacturing
Manufacturing runs on timing. Downtime costs thousands per minute, quality defects compound through the supply chain, and demand forecasting determines whether you're sitting on inventory or missing orders. We build the AI and data systems that make these decisions faster and more accurate.
View industry →Insurance & InsurTech
Insurance runs on decisions: pricing risk, processing claims, detecting fraud. Most carriers still make these decisions with rules written a decade ago. We build AI systems that score risk in real-time, automate 80% of claims processing, and catch fraud patterns human reviewers miss.
View industry →Healthcare & Life Sciences
Healthcare teams run on fragmented systems, manual handoffs, and data that doesn't move between departments. We design AI-powered clinical workflows, patient engagement platforms, and data infrastructure that meets HIPAA requirements and ships into production.
View industry →SaaS & Tech Products
SaaS companies need to ship AI features fast, scale infrastructure without downtime, and grow efficiently. We build the platform architecture, AI integrations, and growth systems that let product teams move at startup speed with enterprise reliability.
View industry →Frequently asked questions
It depends on the problem. Classification tasks can start with 1,000-10,000 labeled examples. Forecasting needs 2+ years of historical data. We assess feasibility in the first week.
Automated monitoring tracks prediction accuracy, data drift, and feature importance changes. When performance drops below threshold, retraining triggers automatically.
Yes. We build explainability into every model: SHAP values, feature importance, and decision breakdowns that your team and regulators can audit.
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Prediction systems that run 24/7. Not proof-of-concepts gathering dust.