What we build
ML, generative AI, computer vision, and MLOps — wired into operations, not slideware.
Machine learning
Prediction wired into operations: churn before it happens, credit and fraud risk before it costs, pricing that responds to demand, forecasts your inventory can trust. Every model ships with a baseline, an accuracy target, and a retraining schedule — because unmonitored models decay silently.
Generative AI & NLP
Document intelligence that reads contracts and invoices, semantic search that understands intent instead of keywords, RAG pipelines that answer from your private data with citations, and assistants trained on your business context. Plus sentiment analysis, chatbots, and voice interfaces.
Computer vision & deep learning
Classification, similarity, and defect detection with CNNs and transformer architectures. In production: a diamond-similarity engine combining Random Forest classification, K-Means clustering, GrabCut feature extraction, and HSV/LAB color analysis — 80% accuracy, evaluation 60% faster than expert review.
MLOps & model governance
Version control for models and data, deployment pipelines, drift detection, monitoring dashboards, and audit trails mapped to your compliance needs. This is the difference between an AI feature and an AI liability.
Deterministic rules that never change. Datasets too small to learn from. Decisions requiring full explainability under regulation where a model can't provide it.
We've talked clients out of ML projects — a system that shouldn't exist is expensive at any accuracy.
In production: a diamond-similarity engine combining Random Forest classification, K-Means clustering, GrabCut feature extraction, and HSV/LAB color analysis — 80% accuracy, evaluation 60% faster than expert review.
Discuss your project80%
Vision accuracy
60%
Faster evaluation
MLOps
Governed & monitored
Less than you fear, more than a spreadsheet. The readiness audit answers it precisely: what you have, what's usable, what's missing, and whether the project should proceed.