Kognition
Kognition AI security stops threats in real-time.
Transform legacy security into intelligent protection that pays for itself. Kognition AI integrates seamlessly with existing cameras and access control - no costly rip-and-replace required.
Why Security Leaders Choose Us:
✓ 24/7 AI Guardian that never misses threats or calls in sick
✓ Works with Axis, Hanwha, Avigilon, Genetec, Milestone, and other popular platforms and devices.
✓ Real-time alerts deliver actionable intelligence in seconds
✓ Easy to deploy enterprise-grade security
Perfect for corporate campuses, schools and universities, office buildings, hospitals, and retailers seeking modern security to reduce risk and improve staff, student, and tenant safety.
Transform your security team from reactive responders to proactive guardians with Kognition AI - schedule a demo today!
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Ango Hub
Ango Hub is a quality-focused, enterprise-ready data annotation platform for AI teams, available on cloud and on-premise. It supports computer vision, medical imaging, NLP, audio, video, and 3D point cloud annotation, powering use cases from autonomous driving and robotics to healthcare AI.
Built for AI fine-tuning, RLHF, LLM evaluation, and human-in-the-loop workflows, Ango Hub boosts throughput with automation, model-assisted pre-labeling, and customizable QA while maintaining accuracy. Features include centralized instructions, review pipelines, issue tracking, and consensus across up to 30 annotators. With nearly twenty labeling tools—such as rotated bounding boxes, label relations, nested conditional questions, and table-based labeling—it supports both simple and complex projects. It also enables annotation pipelines for chain-of-thought reasoning and next-gen LLM training and enterprise-grade security with HIPAA compliance, SOC 2 certification, and role-based access controls.
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Visual Layer
Visual Layer is a platform for working with large volumes of image and video data. It supports visual search, filtering, tagging, and dataset structuring across raw files, metadata, and labels. No code is required, and both technical and non-technical teams use it in production. Common applications include curating datasets for machine learning, auditing visual content for compliance, reviewing surveillance material, and preparing media for downstream platforms.
The platform detects duplicates, mislabeled items, outliers, and low-quality files to improve data quality before model training or operational decision-making. It is model-agnostic, supports both cloud and on-premise deployment, and is built by the creators of Fastdup, the widely used open-source tool for visual deduplication.
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