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Obz AI empowers organizations to monitor, secure, and optimize their computer vision models in production. With Obz AI, you can deploy computer vision systems reliably and responsibly.
  • Continuously track the performance of computer vision models — including vision transformers (ViT), convolutional neural networks (CNN), and more — with customizable metrics and detailed dashboards
  • Inspect data quality across all stages, from input pipelines to feature stores, for both batch and streaming vision data
  • Detect and diagnose key issues like outliers, model drift, degraded accuracy, bias, and data anomalies
  • Collaborate and improve model performance using feedback loops and cross-team workflow features

Quickstart

Overview of Obz AI’s major functionalities

Tutorial

Explaining and monitoring a ImageNet Classifier

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Data Inspector

Modern computer vision AI systems are processing diverse data. As data pipelines grow more complex and handle increasingly divergent sources, they are vulnerable to silent failures and data drift. Data Inspector addresses these challenges by automatically extracting informative features from images and employing advanced outlier detection techniques. This empowers users to pinpoint anomalies, identify data quality issues, and monitor changing patterns in their image data — all before these problems undermine downstream analytics or model performance. By continuously monitoring shifts in distributions and looking for novel and unusual samples, Data Inspector offers early warnings for potential problems. It is an essential tool for teams who want to ensure integrity in their image pipelines and guard against data drift and concept drift, two pervasive threats to machine learning in production. With Data Inspector, you can proactively manage and validate your data, building a resilient foundation for your AI and analytics initiatives.

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AI Explainability

Today’s businesses increasingly rely on AI systems to analyze and interpret complex data, such as images, to drive decision-making and automate critical workflows. However, the growing adoption of advanced machine learning models brings a significant challenge: the black-box nature of AI. When deployed in production, these opaque systems make decisions without providing visibility into their internal processes. This lack of explainability exposes organizations to potential operational risks, unchecked biases, and compliance gaps that can escalate into costly issues over time. Explainability is a critical component of modern AI system. Monitoring, understanding, and validating AI-driven outcomes are essential not only for ensuring trust and reliability in production, but also for meeting evolving regulatory requirements around transparency and accountability. Obz AI deliver advanced, easy-to-deploy explainable AI (XAI) methods that seamlessly integrate into your workflows and provide clear visualizations of image-based model decisions. By adopting robust XAI tools, your organization can stay ahead of compliance demands, build stakeholder trust, and ensure your CV systems remain robust and intelligent.
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