Featured insights

We build Gen AI solutions to automate key invoice management tasks such as invoice validation, discount verification, exception handling and more. These solutions reduce manual errors, speed up billing cycles, and ensure accuracy in financial transactions, enhancing operational efficiency and enabling supply chain teams to focus on strategic planning.

We develop Gen AI solutions to streamline logistics operations – from shipment scheduling and tracking to delivery confirmation and exception resolution. These solutions automate customer notifications, enhance coordination across carriers and warehouses, and provide real-time visibility, helping organizations improve service levels and reduce order fulfillment delays.

We develop Gen AI solutions to streamline returns and post-delivery issue resolution – from return authorization and tracking to root cause analysis and corrective action planning. These solutions can identify recurring problems and generate insights to improve processes, reducing turnaround time, lowering return-related costs, and enhancing customer and partner satisfaction.

Our Gen AI solutions can support customer service operations across the supply chain by automating order status inquiries, shipment updates, returns processing, and issue resolution. These solutions analyze service requests, generate timely and accurate responses, and prioritize support requests, reducing manual effort, speeding up response times, and improving service quality across order and delivery operations.

We design and deploy Gen AI solutions using frontier models tailored for supply chain use cases. Our capabilities include retrieval-augmented generation (RAG), prompt and context engineering, model fine-tuning, domain adaptation, and agentic workflows — ensuring solutions are secure, scalable and aligned with business goals.

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, regression solutions, and anomaly detection capabilities.

We use deep learning to address complex language, vision, and forecasting and inference challenges. Our experience with convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models allows us to deliver advanced solutions that handle multimodal data such as text, images, and audio.

We build NLP solutions that analyze, interpret and generate natural language with contextual depth. Our core capabilities include semantic analysis, entity extraction, sentiment classification and advanced language generation — converting unstructured text into structured, actionable insights.

Our data science practice applies statistical methods and analytical techniques, including Bayesian approaches, to extract meaningful insights from complex datasets. We excel in experimental design, feature engineering, and comprehensive model evaluation, ensuring your AI solutions are reliable, interpretable, and built on solid analytical foundations.

We implement computer vision solutions to analyze and extract meaning from images and videos. Our expertise includes image classification, object detection, segmentation and optical character recognition (OCR) — enabling intelligence from visual data.

We implement scalable data labeling processes essential for supervised learning. Our capabilities include structured annotation processes, built-in quality checks, and specialized tools for labeling text, images, and video — ensuring high-quality training data for accurate, reliable AI model development.

We build robust operational frameworks to manage the full AI model and agent lifecycle. Our expertise spans automated training pipelines, version control, monitoring frameworks and deployment strategies that ensure scalable, governed, high-performing transitions from development to production.

We apply specialized algorithms to analyze time series data. Our core strengths include identifying trends, modeling seasonality and generating forecasts — enabling predictive insights for use cases such as demand planning, financial modeling, operations optimization and predictive maintenance.