Data & Statistical Insight
Rigorous exploratory analysis and statistical testing that turns raw operational data into decisions you can defend.
See methods
ML · Computer Vision · Generative AI
Applied AI that earns its place in production.
We help finance, healthcare, manufacturing, security and IT teams turn machine learning, computer vision and generative AI into measurable business outcomes — built rigorously, deployed reliably.
Machine Learning
Deep Learning
Computer Vision
Generative AI
Graph Intelligence
MLOps
What we build
Six capabilities, matched to the problem
We're full-stack across modern AI — classical machine learning, deep learning, generative AI and graphs — so the method fits the decision, not the other way around.
Predictive Machine Learning
Classification, regression and risk scoring with models that are validated, balanced and explainable — not just accurate on paper.
See methodsComputer Vision & Deep Learning
Image classification, detection and inspection — with attention maps that show why the model made each call.
See methodsGenerative AI & RAG
Large language models grounded in your own documents, with citations and evaluation so the answers are trustworthy enough to act on.
See methodsGraph Intelligence
Model the relationships and networks tabular data can't capture — fraud rings, supply chains, attack paths.
See methodsMLOps & Deployment
From notebook to production — models served behind APIs, containerized, monitored and built to scale.
See methods
Where we apply it
Built for five high-stakes domains
The same rigorous toolkit, focused on the business problems that matter in your industry.
Selected work
Proof, not promises
A look at the kind of systems we deliver — evaluated honestly and built to be trusted.
Investment research RAG over 868 pages of market reports
An engineered retrieval pipeline — token-aware chunking, a local embeddings model, diversity-aware retrieval and a cited analyst persona — turned five dense sector reports into a citable Q&A engine for investment decisions.
0.93+
composite answer-quality score
>90%
retrieval accuracy target met
5
energy sectors unified
Explainable 4-class brain-MRI classifier
Transfer learning with class-balanced loss and stacked ensembling, tuned for recall so tumors aren't missed — paired with attention heatmaps so clinicians can see the model's reasoning.
4-class
glioma · meningioma · pituitary · none
Heatmaps
per-prediction explainability
Recall-first
minimizes false negatives
Imbalanced fraud & threat detection
Random Forest and gradient-boosting ensembles with class-imbalance handling, cross-validated and tuned to hold precision and recall in balance — so real fraud is caught without burying teams in false alarms.
ROC-AUC
tuned & cross-validated
Balanced
precision & recall held in balance
Explainable
feature-importance rankings
How we work
From business decision to production
01
Frame the decision
We start from the business decision and the metric that moves it — not the model.
02
Prove it on your data
A focused proof-of-value on real data, evaluated honestly against a baseline.
03
Engineer for trust
Explainability, evaluation and guardrails built in, so stakeholders can rely on it.
04
Deploy & hand over
Production deployment, monitoring and knowledge transfer — you own what we build.
Evaluated, not assumed
Every model is measured against a baseline with the right metric for the decision.
Explainable by default
Attention maps, feature importance, citations — stakeholders see why, not just what.
Built to ship
We close the gap from notebook to production with real deployment and monitoring.
Full-stack AI
Classical ML, deep learning, generative AI and graphs — matched to the problem.
Have a problem worth solving with AI?
Tell us the decision you're trying to make. We'll tell you, honestly, whether AI is the right tool — and how we'd prove it.