Grafana
Grafana Labs provides an open and composable observability stack built around Grafana, the leading open source technology for dashboards and visualization. Recognized as a 2025 Gartner® Magic Quadrant™ Leader for Observability Platforms and positioned furthest to the right for Completeness of Vision, Grafana Labs supports over 25M users and 5,000+ customers.
Grafana Cloud delivers the full power of Grafana’s open and composable observability stack—without the overhead of managing infrastructure. As a fully managed SaaS offering from Grafana Labs, it unifies metrics, logs, and traces in one place, giving engineering teams real-time visibility into systems and applications. Built around the LGTM Stack—Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics—Grafana Cloud provides a scalable foundation for modern observability.
With built-in integrations for Kubernetes, cloud services, CI/CD pipelines, and OpenTelemetry, Grafana Cloud accelerates time to value while reducing operational complexity. Grafana Cloud also supports OLAP-style analytics through integrations with data warehouses and analytical engines like BigQuery, ClickHouse, and Druid—enabling multi-dimensional exploration across observability and business data. Teams gain access to powerful features like Adaptive Metrics for cost optimization, incident response workflows, and synthetic monitoring for performance testing—all within a secure, globally distributed platform. Whether you’re modernizing infrastructure, scaling observability, or driving SLO-based performance, Grafana Cloud delivers the insights you need—fast, flexible, and vendor-neutral.
Learn more
Ango Hub
Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality.
Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset.
Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.
Learn more
SimpleCV
SimpleCV is a freely available framework designed for the creation of computer vision applications. It provides users with access to a variety of powerful libraries, including OpenCV, without requiring them to grasp complex concepts such as bit depths, file formats, color spaces, buffer management, eigenvalues, or the distinctions between matrix and bitmap storage. This framework streamlines the process of computer vision. The capabilities of SimpleCV extend far beyond the basics outlined here. For those interested in diving deeper, we encourage you to explore our tutorial for comprehensive guidance. Additionally, a wealth of examples can be found in the SimpleCV directory within the examples folder, which is also available for download from our site. As an open-source framework, SimpleCV comprises an array of libraries and software tools that facilitate the development of vision applications. It enables users to interact with images or video feeds from various sources such as webcams, Kinects, FireWire and IP cameras, or even mobile devices. Ultimately, it empowers developers to create software that not only perceives the environment but also interprets it effectively.
Learn more
Azure Computer Vision
Enhance the visibility of your content, streamline the extraction of text, analyze videos on the fly, and develop user-friendly products by incorporating visual capabilities into your applications. Leverage visual data processing to tag content with relevant objects and concepts, retrieve text, produce descriptions for images, manage content moderation, and interpret human movement within physical environments. This approach is accessible to everyone, regardless of their machine learning background. By adopting these technologies, you can significantly improve user engagement and interaction with your products.
Learn more
