We design and implement Gen AI solutions using foundation models tailored to a wide range of enterprise use cases. Capabilities include retrieval-augmented generation (RAG), prompt engineering, model fine-tuning and domain adaptation, as well as agentic workflow design – ensuring solutions are secure, scalable and aligned with business objectives.

We leverage statistical and algorithmic approaches to uncover hidden patterns and relationships within your data. Our expertise encompasses supervised, unsupervised, and reinforcement learning, enabling us to develop powerful predictive systems, classification solutions, and anomaly detection capabilities.

We apply deep learning techniques to build solutions that address complex challenges in language, vision and forecasting. Our proficiency includes working with convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models to deliver advanced pattern recognition across multimodal inputs such as text, images, and audio.

We build NLP solutions to analyze, interpret and generate natural language with nuances. Core capabilities span semantic analysis, entity extraction, sentiment classification and advanced language generation, transforming unstructured text into structured, actionable intelligence.

Our data science practice delivers reliable, interpretable models using advanced statistical techniques and rigorous experimentation. We apply Bayesian inference, feature engineering and outcome validation to generate actionable insights from complex datasets.

We implement cutting-edge computer vision algorithms to interpret and analyze visual information from images and video. Our expertise covers image classification, object detection, instance/semantic segmentation and optical character recognition (OCR), unlocking valuable intelligence from your visual data assets.

We implement scalable data labeling processes essential for supervised learning applications. Our capabilities include structured annotation workflows, quality assurance procedures, and specialized tooling for text, image, and video labeling, ensuring the high-quality training data critical for developing accurate and reliable AI models.

We design and implement robust operational frameworks for AI model lifecycle management. Core expertise includes automated model training pipelines, versioning systems, monitoring frameworks, and deployment strategies that enable reliable scaling from development to production while maintaining governance and performance standards.

We implement specialized algorithms for processing temporal data sequences. Core capabilities include trend detection, seasonality modeling, and forecasting techniques that deliver predictive insights for applications in demand planning, financial modeling, operational optimization, and predictive maintenance.