Machine Learning models that perform in a demo and fall apart three months later aren’t useful. Bajco Tech builds models trained on your data, integrated into your systems, and monitored long after deployment.
A model that scores well in testing can still fail in production — real-world data is messier, edge cases are unpredictable, and without monitoring, nobody notices drift until the decisions it’s driving are already wrong. Most Machine Learning projects don’t fail at the algorithm. They fail at everything that comes after it.
Feasibility analysis, data audit, and ROI assessment before any model gets built — because the wrong problem solved well is still the wrong problem.
Custom algorithms built around your specific patterns, edge cases, and operational context — supervised, unsupervised, or reinforcement learning as needed.
Drift detection, retraining pipelines, and version control — so the model running in six months is as reliable as the one that shipped on day one.
Custom model development, supervised and unsupervised learning, reinforcement learning, training, validation, and production integration.
Feasibility and ROI analysis, data readiness assessment, algorithm selection, and a deployment strategy built around your team.
Continuous evaluation, retraining pipelines, drift detection, real-time alerting, and rollback mechanisms when corrections are needed.
MLOps pipelines, CI/CD for ML, scalable model hosting on cloud or on-prem, API integration, and containerization via Docker and Kubernetes.
Predictive analytics, recommendation systems, anomaly detection, NLP, image and video analysis, and time-series modeling.
If your team is buried in repetitive tasks, sitting on data nobody has time to use, or stuck with an AI pilot that never got real adoption — let’s talk.
Tell us about your goals and challenges. Book a call to discover how far your business can go and how to get there fast.