Data Science & ML Research That Solves Real Problems, Not Textbook Problems
Moving beyond basic analytics to predictive intelligence. We leverage complex data ecosystems to extract non-obvious, actionable business value.
Data Science Capabilities
Predictive Analytics & Forecasting
High-accuracy time-series forecasting models to predict demand, anticipate market shifts, and optimize inventory holding costs.
Customer & Behavioral Modeling
Deep reinforcement learning and clustering algorithms to understand extreme edge cases in customer behavior, predicting churn before it happens.
Anomaly & Fraud Detection
Graph-based neural networks and isolation forests identifying sophisticated, multi-actor fraud rings in real-time across billions of transactions.
NLP & Text Analytics
Extracting structured intent, sentiment, and causal relationships from massive corpuses of unstructured text, emails, and financial documents.
Recommender Systems
Two-tower models and extreme multi-label classification delivering hyper-personalized content and product recommendations at scale.
Computer Vision Systems
Custom YOLO-based object detection and image segmentation pipelines for automated quality control, remote sensing, and medical imaging.
Our ML Research Methodology
01: Problem Framing
We spend an outsized amount of time translating your business objective into a rigorous mathematical problem statement.
02: Data Engineering Setup
Building the foundation. We construct secure, scalable ETL pipelines and feature stores ensuring reproducibility.
03: Model Building
Iterative experimentation. We build everything from simple XGBoost baselines to complex deep learning architectures, tracking every run.
04: Evaluation
Rigorous backtesting against out-of-sample data. We don't just optimize for accuracy, but also for precision, recall, and business ROI.
05: Deployment
Containerizing models as microservices. We deploy shadow models alongside existing logic for seamless A/B transition.
06: Monitoring
Setting up drift detection alerts. When model performance gracefully degrades due to changing real-world distributions, we retrain.
The Tools We Trust in Production
We remain stack-agnostic, choosing the right combination of state-of-the-art research models and bulletproof enterprise engineering tools for every project.
AI / ML Frameworks
LLMs & Orchestration
Vector Databases
Cloud & MLOps
Backend & Data
Frontend & Mobile
Sector-Specific Intelligence,
Proven Results
Research Outcomes
Global Supply Chain Optimization
Built a probabilistic forecasting model for a logistics giant, cutting safety stock holding costs by $14M annually.
Payment Fraud Network
Deployed a graph neural network that reduced false positives in high-value B2B transactions, saving analyst review bandwidth.
Clinical Trial Matching
Developed a biomedical NLP pipeline matching patients to complex inclusion criteria across thousands of oncology trials.
Common Questions
Everything you need to know about our research methodology, engagement models, and AI engineering practices.
Business Intelligence tells you what happened in the past. Data Science tells you what *will* happen in the future and *why* it will happen. We move your organization from reactive reporting to proactive, algorithmic decision-making.