Roboflow logo

Roboflow

Emerging#15 in Artificial Intelligence

SF computer vision platform for dataset management, annotation, training, and deployment serving 250K+ developers; $40M OpenAI Fund-backed at $200M valuation competing with Scale AI for CV development tooling.

Best for: Computer VisionEmerging, rapid growth
35
AI Score
Grade D↑ Trending
AI Visibility Score (Beta)
Artificial IntelligenceComputer VisionWebsiteUpdated March 2026

Brand Intelligence Graph

Capabilities
Computer Vision

Company Overview

About Roboflow

Roboflow is a San Francisco-based computer vision platform — backed with $40 million raised from OpenAI Fund, Craft Ventures, and Y Combinator at an estimated $200 million valuation — providing developers, ML engineers, and enterprises with a complete toolkit for building, training, and deploying custom computer vision AI models: dataset management, image and video annotation (manual and AI-assisted), model training, evaluation, and deployment to edge devices, cloud APIs, and web applications. Founded in 2019 by Brad Dwyer and Joseph Nelson, Roboflow serves 250,000+ developers and 50,000+ organizations with a community-driven model that includes the Roboflow Universe (public dataset repository with 100,000+ computer vision datasets).

Business Model & Competitive Advantage

Roboflow's end-to-end platform eliminates the infrastructure overhead that custom computer vision development previously required: data scientists collecting images for a custom product defect detector previously needed to build annotation pipelines, manage version control for labeled datasets, set up training infrastructure (GPUs, experiment tracking), and implement deployment serving separately. Roboflow consolidates this into a single platform — annotate images using the interface, run training with a few clicks, and deploy the model to an API or Raspberry Pi device. The RF100 benchmark (standardized evaluation across 100 computer vision datasets) enables model comparison and has become a community standard for measuring computer vision model progress.

Competitive Landscape 2025–2026

In 2025, Roboflow competes in the computer vision development platform market with Scale AI ($1B+ valuation, data labeling and AI infrastructure), Landing AI (Andrew Ng's computer vision company), and NVIDIA's Metropolis (AI for edge vision) for computer vision tooling adoption. The open-source Supervision library (released by Roboflow, 25,000+ GitHub stars) has become a standard toolkit for computer vision practitioners, driving developer community growth. OpenAI Fund's investment reflects the conviction in computer vision tooling as AI applications expand beyond text to visual domains. The 2025 strategy focuses on growing enterprise customers for quality inspection (manufacturing, agriculture, logistics), building the video analytics capabilities alongside image detection, and expanding the foundation model fine-tuning workflow for the organizations adapting GPT-4V and similar models to domain-specific tasks.

Founded
2019
Curated content • Fact-checked and verified

Recent Activity

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Material Event filed 2026-05-20

blog_post
PPE Detection with AI: Real-Time Worker Safety Monitoring

Learn how to automate workplace safety monitoring. Build a real-time PPE detection pipeline using RF-DETR and Roboflow Workflows to track helmets and vests.

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Build a Real-Time Traffic Light Detection System

Learn how to build a real-time traffic light detection system.

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Golf Swing Analysis with Vision AI

Analyze golf swing mechanics automatically using Roboflow 3.0 keypoint detection and Gemini 2.5 Flash in Roboflow Workflows.

blog_post
Computer Vision MCP: How to use Roboflow MCP

Learn how to use the Roboflow MCP server with Claude Code to build a bird species monitoring app, from uploading images and and generating dataset version to training an RF-DETR model and deploying a Workflow, all from your terminal.

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Pothole Detection with RF-DETR

Discover how to build a pothole detection pipeline. Use RF-DETR and ByteTrack in Roboflow Workflows to automate road hazard tracking and repair prioritization.

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GPT-5.5: Vision Benchmarks & Use Cases

Explore OpenAI GPT 5.5 vision benchmarks. Learn how its new high-resolution encoder improves document parsing and how to use it in Roboflow Workflows.

blog_post
Tracking Baseball Games with AI: Dynamic Field Analytics

Build a high-speed computer vision pipeline using RF-DETR and OC-SORT to extract player and ball telemetry data.

blog_post
Automate Food Service with AI

Two tutorials for automating food quality with computer vision: end-line plating QA with Gemini 3, and a packaging line monitor with RF-DETR and ByteTrack.

blog_post
High-Speed Analytics: Tracking Table Tennis Movements with RF-DETR and OC-SORT

Build a high-speed computer vision pipeline using RF-DETR and OC-SORT to generate sports analytics.

blog_post
Pickleball Player Performance Analytics with Roboflow

Analyze pickleball player positioning and tactics automatically using RF-DETR, Roboflow Workflows, and Claude.

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Hockey Player Tracking with Roboflow

Learn how to build a hockey tracking pipeline. Use RF-DETR and ByteTrack in Roboflow Workflows to track players and visualize movement trails.

Key Differentiators

Emerging Innovator

Roboflow is an emerging player bringing innovative solutions to the AI & Machine Learning market.

Frequently Asked Questions

Estimated Visibility Trend (Beta)

Simulated 8-week rolling score

35
↑ Trending

Based on estimated brand signals. Historical tracking coming soon.

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