Harbor ML provides enterprise data infrastructure for training physical AI systems. The platform combines automated sensor data ingestion, AI-assisted pre-labeling, and human-in-the-loop reinforcement learning from human feedback (RLHF) to produce high-quality training datasets. Harbor ML integrates with enterprise AI environments to accelerate development of robotics, computer vision, and autonomous systems.
- Industries
- Automotive
- Media & Entertainment
- Software and platform applications
- Technology (Industry)
- Topics
- AI and ML
- Application development
- Automation
- Blockchain
- Cloud
- Data storage
- IT infrastructure
- Deployment types
- SaaS
- On-premises
- Languages supported
- Swedish
- English
- Regions and countries supported
- Africa -
- Americas -
- Asia -
- Europe -
- Oceania -
IBM Cloud integration enables global video distribution with low latency and high performance.
Automated and human-in-the-loop labeling pipelines generate high-quality datasets for training robotics, vision, and AI models.
RLHF workflows enable humans to review, rank, and correct model outputs, improving accuracy and safety of AI systems.
Unified data pipelines ingest, process, and prepare real-world sensor data for scalable AI model training.
Automated pre-labeling tools accelerate dataset creation while human reviewers verify and refine annotations for high-quality AI training data.
Integrated feedback pipelines allow humans to review, rank, and correct model outputs to improve training accuracy and reliability.
Scalable pipelines ingest and process real-world sensor, video, and telemetry data for robotics and computer vision training datasets.
Unified infrastructure organizes, manages, and prepares large datasets for scalable AI model training and continuous improvement.
Interactive documentation showing detail of Harbor ML build out for enterprise clients.
Walkthrough of Harbor ML’s AI-assisted annotation platform showing automated labeling, human review workflows, and dataset generation.
Demonstration of Harbor ML’s human-in-the-loop RLHF pipelines used to review, rank, and improve AI model outputs.
Information about the companies and solutions listed in this directory is provided by each company and is not validated by IBM unless otherwise noted.