Roboflow Vision AI Platform

Roboflow, Inc. was launched in 2020 by Brad Dwyer and Joseph Nelson and went through Y Combinator's S20 batch; its legal address is in Des Moines, Iowa, with teams in San Francisco, New York and Brazil. It gives developers and enterprises the tools to build computer vision applications and run them in production.

The platform covers the full pipeline: Annotate offers AI-assisted labeling with frontier models such as SAM 3, Train fine-tunes models including the open-source RF-DETR and YOLO families, Workflows chains models with business logic and connects to industrial systems, and Deploy runs high-speed inference on images or live video in the cloud or on edge devices. A Vision AI Agent and an MCP server let teams build applications from natural language prompts. Universe hosts public datasets and models, and open-source libraries such as supervision and inference are widely used.

• Annotate: AI-assisted labeling with frontier models and custom filters.
• Train: fine-tuning of RF-DETR, YOLO26, YOLO11 and other models on custom datasets.
• Workflows: low-code chaining of models, logic and actions with connections to industrial systems.
• Deploy: high-speed inference on images and live video in the cloud or at the edge.
• Vision AI Agent and MCP: build vision applications from prompts in tools such as Claude, Cursor and ChatGPT.
• Universe and open source: public datasets and models plus libraries such as supervision and inference.

Electronics, furniture and building material factories in Vietnam can train defect detection models on their own line images and run them on edge devices. Logistics and port operators can count and track goods, containers or vehicles from existing cameras. System integrators and AI startups can prototype vision solutions for clients quickly using the free tier and open-source models.

Roboflow states that more than 2 million developers build on it and that over half of the Fortune 100 use the platform. Teams can go from raw images to a deployed model in one tool instead of stitching labeling, training and serving systems together. Edge-optimized inference lets manufacturers run models at many sites, as USG does across more than 50 plants. A free tier lowers the cost of pilots before enterprise rollout.

Open vision foundation models and fast detectors are lowering the barrier to computer vision, shifting the bottleneck to data, deployment and integration with plant systems. Manufacturers in Vietnam and Southeast Asia are adopting camera-based quality inspection, safety monitoring and inventory tracking as labor costs rise and export customers demand consistent quality.

Launched in 2020 by Brad Dwyer and Joseph Nelson; Y Combinator S20. Raised a USD 40 million Series B in November 2024 led by GV with Craft Ventures and Y Combinator. Other investors include Valor Equity Partners, Frontline Ventures and Lachy Groom. SOC 2 Type II compliant; AWS Partner and AWS Qualified Software.