Services
What we do
We focus on three things: building ML systems, setting up data infrastructure, and advising on AI strategy. We don’t do everything — we do these well.
Machine Learning Development
Custom ML models built for your specific problem, deployed to production with monitoring and retraining pipelines. We work on fraud detection, demand forecasting, churn prediction, anomaly detection, NLP, and computer vision.
What we deliver
- Problem scoping and data assessment
- Feature engineering and model training
- Evaluation against your current process
- Production deployment with CI/CD
- Monitoring, alerting, and automated retraining
- Documentation and team handoff
Stack
Python, PyTorch, TensorFlow, scikit-learn, Kubernetes, MLflow, Weights & Biases
Timeline
8-16 weeks
Data Engineering & Analytics
Building the data infrastructure that makes ML possible. Pipelines, warehouses, quality frameworks, and dashboards. If your data is fragmented, inconsistent, or inaccessible, we fix that before anyone trains a model.
What we deliver
- Data audit and architecture design
- ETL/ELT pipeline implementation
- Cloud data warehouse setup and migration
- Data quality and validation frameworks
- BI dashboards and reporting
- Real-time streaming pipelines where needed
Stack
Apache Spark, Airflow, dbt, Snowflake, BigQuery, Kafka, PostgreSQL
Timeline
6-14 weeks
AI Strategy & Advisory
Honest assessment of where AI fits your business — and where it doesn’t. We identify high-impact use cases, evaluate your data readiness, and create a realistic implementation plan. No 80-slide decks. No inflated ROI projections.
What we deliver
- Current-state assessment and data audit
- Use case identification and prioritization
- Technical feasibility evaluation
- Implementation roadmap with realistic timelines
- Build-vs-buy recommendations
- Team capability assessment
Have a project in mind?
Tell us about your problem. We’ll be honest about whether we can help — and if we can’t, we’ll point you in the right direction.
Get in touch