Strategy & Roadmapping
Develop strategies and roadmaps to scale ML across the organization, focused on high-impact business use cases.
Responsible Engineering
Provide guidance on developing frameworks to build ML solutions upholding transparency, fairness, interpretability and compliance.
Change Management for Adoption
Formulate plans to drive organizational change, user adoption, and new skills required to leverage ML solutions.
Operations Strategy
Recommend strategies for ongoing model monitoring, retraining, explainability and governance required for maintaining machine learning reliability and value.
Data Strategy
Assess data infrastructure and workflows needed to prepare quality training data and drive ML model accuracy.
Our R&D team explores the latest advances to evolve our ML solutions and integrate proven practices for maximizing model robustness.
Computer vision
Architect optimized convolutional neural networks for computer vision tasks like image classification, object detection, semantic segmentation.
Natural Language Processing
Create intelligent natural language interfaces and chatbots leveraging techniques like text classification, named entity recognition, sentiment analysis.
Recommendation systems
Develop personalized product recommendation engines leveraging collaborative and content-based filtering algorithms.
Forecasting
Produce accurate demand forecasts, predictive analytics and time series predictions applying statistical modeling and deep learning techniques.
Anomaly detection
Enable real-time anomaly detection for critical use cases like fraud detection, network intrusion detection, fault detection.
Regression & classification
Implement proven supervised learning techniques like random forests and SVM for regression, classification, predictive modeling.
Clustering
Discover unseen patterns and groupings in complex datasets by applying unsupervised learning algorithms like K-means clustering.
Reinforcement learning
Engineer systems that can optimize complex sequential decision processes and learn behaviors like game strategy, logistics coordination.
Building accurate ML requires specialized expertise across data, infrastructure, development, training, and responsible practices. Our teams leverage proven techniques to optimize model accuracy.
We have over a decade of experience developing ML solutions using leading approaches like deep learning across industries. Our experts leverage proprietary frameworks refined over thousands of cycles to engineer custom models optimized for specific problem spaces.
This full-stack capability allows rapidly delivering production-grade ML that provides accurate predictions while upholding transparency and
fairness standards. Our rigorous processes ensure models reliably scale while minimizing ongoing maintenance.
Optimize energy demand forecasting
Apply time series modeling techniques to better predict peak loads and improve generation scheduling.
Analyze insurance claim documents
Use computer vision and NLP to extract information from unstructured claims data like photos and adjustor notes.
Automate legal document review
Use NLP to accurately classify and extract information from contracts and case documents.
Recommend learning content
Develop recommendation systems using precise student preference models to deliver personalized eLearning content.
Moderate inappropriate user-generated content
Carefully tune classification models to identify policy violations without over-censoring.
Optimize traffic flow
Leverage computer vision and time series modeling on camera feeds and traffic data to forecast accidents and congestion.
Co-creating the world we want to live in
From today's trendsetting brands to the startups shaping tomorrow, we collaborate with organizations we respect and applaud. Over two decades, our commitment has been to jointly shape a more open, resilient, and optimistic world alongside our clients.
