Object Detection
Improve your competitiveness by leveraging computer vision techniques for accurate and efficient object detection in various applications such as autonomous vehicles, surveillance systems, and retail analytics.
Image Classification
Utilize computer vision algorithms to recognize and classify images, enabling you to gain insights from large datasets.
Video Analysis
Leverage computer vision technologies to extract valuable information from videos, allowing you to automate detect and track objects, and analyze behavior in real-time.
Document Analysis
Automate document processing tasks using computer vision, such as extracting information from invoices, forms, and contracts, leading to improved efficiency, reduced errors, and faster decision-making.
Anomaly Detection in Visual Data
Apply computer vision techniques to detect anomalies in visual data, enabling you to identify irregularities in manufacturing processes, monitor equipment health, and enhance quality control systems.
Whether you want to build a Proof-of-Concept (POC) or solve a large organizational pain point using data, we can improve your decision-making using Machine Learning or Data Science.
Product Forecasting
We’ve done multiple forecast models for our diverse base of retail customers. Our models aren’t only tied to past sales data but incorporate contextual information relevant to explain the demand of each product.
Computer Vision
Extract insights from your photos or videos. Be able to identify and track new insights or automate manual processes.
No Data works without Data Engineering. As Data Scientists and Data Engineers, we understand how to manage and organize data to fit your business needs.
Cost Optimization
Optimize your cloud infrastructure to reduce your costs.
Computer Vision
Build data pipelines and aggregate data from different sources. Combine data with external datasets for new KPIs.
MLOps are a crucial part of any Data & AI development. Because most companies stay in the POC stage, we are experts in setting up state-of-art MLOps best practices and helping you leaving the never-ending POC loop.
Model Monitoring and Retraining
Investigate your model drift and retrain it based on triggers.
Pipeline Testing
Make sure that your deployed model receives exactly the same type of data structure that you used on the development phase.