IBM vs Labelbox

Protects enterprise data across AI agents, applications and endpoints against agentic-AI, regulatory and post-quantum risks.

Full-stack application and infrastructure observability powered by agentic AI, including automatic discovery/mapping of GenAI workflows and AI-driven Smart Alerts to reduce alert fatigue.

AI-driven robotic process automation for building intelligent bots that automate business processes, with AI-embedded resilience built into the RPA runtime.

Visual data-science and machine-learning platform for building predictive models, with advanced algorithms, model deployment and open-source framework integration.

Document intelligence platform using OCR, NLP enrichments (entity/sentiment/emotion/category extraction) and LLM integration to automate information discovery from enterprise documents.

A conversational AI platform for building customer-support chatbots and virtual assistants deployed across voice and digital channels.

Platform for building and running AI agents that call enterprise applications on a user's behalf.

An AI coding agent that automates planning, code generation, review and verification across the software development lifecycle, including IBM Z mainframe modernization workflows.

A generative AI assistant for IBM Z mainframe application discovery, code generation, refactoring and modernization.

An agentic AI IT-operations platform that unifies observability, optimization and automated remediation across applications, infrastructure and networks.

Studio for building, tuning and deploying model-based applications on IBM and third-party foundation models.

A governance platform providing real-time visibility, policy enforcement and accountability tracking for AI models and agents across the AI lifecycle.

An open hybrid data lakehouse including a built-in Milvus vector database that unifies data access and automates governance for AI and analytics workloads.

Annotate is the data labeling product within Labelbox, providing 10+ built-in editors for multimodal chat, LLM evaluation, prompt/response generation, computer vision and NLP, plus customizable labeling and review workflows and team performance monitoring.

Catalog is Labelbox's data curation and search product providing out-of-the-box search across images, text, video, conversations and documents over metadata, vector embeddings and annotations without building your own vector database infrastructure.

Labelbox's reinforcement-learning platform for developing, evaluating and deploying enterprise specialist agents, connecting RL environments, evaluation systems and a training loop that fine-tunes models from graded rollout trajectories.

Foundry runs third-party foundation models over data already in Labelbox to pre-label and enrich image, text and document datasets without code, routing the predictions to human review; billed as inference cost per model run plus Labelbox Units.

Horizon supplies RL training gyms and evaluations for reasoning, tool use and computer use, using WorldSim to simulate enterprise environments such as GitLab, Jira, CRM, email and chat and to produce calibrated reward and preference signals for post-training.

Alignerr is Labelbox's expert-network product that routes AI training and evaluation tasks to credentialed contributors across 200+ knowledge domains and 40+ countries and returns structured outputs for RL training, RLHF and evaluation workflows.

Terra is Labelbox's robotics data product delivering video, trajectories and multimodal annotations across pre-training, post-training and evaluation stages, including expert teleoperation with action labels and multiple camera perspectives for embodied foundation models.