Micro1 operates a data labeling and AI training platform focused on frontier model development and agent evaluation. The stack reveals heavy investment in LLM orchestration (LangGraph, LangChain, OpenAI, Vertex AI, AWS Bedrock) paired with video annotation infrastructure (CVAT, Labelbox, Encord) and media processing tools (Adobe, DaVinci Resolve), suggesting the core offering sits at the intersection of model training data and multimodal (especially video) evaluation. The hiring surge is concentrated in data (9 roles) and research (9 roles) — a 2:1 ratio that signals rapid scaling of dataset collection and model evaluation capabilities rather than core platform engineering.
Micro1 is a data platform for collecting, annotating, and quality-assuring training datasets for frontier AI models and robotic systems. Founded in 2022 and based in the San Francisco Bay Area, the company operates across three product areas: AI training dataset development (including activity recognition and behavioral recognition), robotics-focused data collection (synchronized sensor video, physical task recording), and compliance-adjacent AI workflows (legal document understanding, fraud detection in task recordings). The platform addresses the gap between synthetic training data and the high-quality, realistic datasets required to train and evaluate next-generation agents. The company is hiring across the United States, Indonesia, and Uganda.
Micro1 uses Python, LangGraph, and LangChain for LLM orchestration; OpenAI, Vertex AI, and AWS Bedrock for model access; CVAT, Labelbox, and Encord for video annotation; Adobe Creative Cloud and DaVinci Resolve for media processing; and Salesforce and HubSpot for business operations.
Active projects include AI training dataset development, robotics systems training, activity and behavioral recognition data collection, video quality audits, synthetic e-commerce simulation, AI compliance workflows, and legal document understanding models.
micro1's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.