Potato

Overview

Potato is an open-source annotation platform for text, audio, images, video, and qualitative data. It suits teams that want to define their own annotation tasks and run them on their infrastructure. Its broad task coverage and included AI assistance make it versatile; self-hosting is the trade-off.

Key features

Tasks are configured in YAML, and Potato’s maker says an annotation interface can be built without programming. That lowers the barrier to custom workflows, though users still need to install and operate the software themselves. The homepage lists 61 annotation types, including classification, spans, bounding boxes, polygons, and qualitative coding, covering work that would otherwise call for separate tools.

Potato also supports annotation of multi-agent teams on an interaction graph and evaluation of computer-use, voice, and video agents. These capabilities make it relevant to teams assessing agent behavior, not only labeling conventional datasets.

AI assistance includes label suggestions, keyword highlighting, pre-annotation, explanation generation, quality checking, and consistency checking. Integrations include OpenAI, Anthropic Claude, Google Gemini, Ollama, HuggingFace, OpenRouter, vLLM, YOLO, and LangChain. These options can help incorporate model assistance into annotation work, while review workflows remain available for checking labels.

For distributed labeling, Potato documents Prolific and Amazon Mechanical Turk integrations, with participant tracking and quality or approval workflows. It imports text, image, audio, video, and PDF or HTML documents; exports include JSON, JSONL, CSV, CoNLL, Hugging Face, COCO, and YOLO. That range is useful when projects span modalities or need output in established dataset formats.

Pricing

Free — free. Potato’s free plan is self-hosted and includes all features, with no paid tiers or usage limits. It is a strong fit for individuals and teams that can manage their own deployment and want the full feature set without subscription costs. There is no managed cloud tier, so the price advantage comes with responsibility for running the software.

Platforms

Potato is available through web, API, and self-hosted deployments, with support for Linux, macOS, and Windows. The quick start uses pip and requires Python 3.7 or later. Local or own-server operation keeps data on users’ infrastructure and supports offline use, which benefits privacy-conscious projects but requires installation and ongoing operation. Support is directed through Discord or documentation, with a team contact email also provided.

Who it's for

Potato is best suited to research groups, data teams, and developers who need varied annotation types, AI-assisted labeling, or agent evaluation and are comfortable running software themselves. Its GPL version 3 or later license permits use, modification, redistribution, and commercial use subject to the license terms. Teams seeking a managed service should look elsewhere.

Pros and cons

• Pros: The free plan includes all features and has no usage limits, making the full platform accessible without tier-based caps.
• Pros: Support for text, image, audio, video, and qualitative data, plus multiple import and export formats, suits varied project pipelines.
• Pros: Local or own-server deployment keeps data on the user’s infrastructure and supports offline work.
• Cons: Self-hosting is the only deployment option, so users must handle installation and operation rather than relying on a managed cloud service.
• Cons: The pip installation requires Python 3.7 or later, which may add setup work for teams without a suitable environment.

Alternatives

Browse Data Labeling Software for more options. Argilla is another free, open-source self-hosted option, with deployment on Hugging Face Spaces or users’ own infrastructure. CVAT is worth considering for its free Community plan for personal use and small teams, or its online free plan with one member, one project, three tasks, and 1 GB of storage.

Label Studio is a freemium option with a free trial. Doccano is a free alternative installable with pip, Docker, or Docker Compose. Datasaur offers a free plan capped at one user, 5,000 labels per year, and 100 MB of storage, with a Growth trial of up to 14 days. Roboflow offers a free tier with 10 monthly credits, described as enough for about 30 model trainings or 80,000 inferences. LightlyStudio has a free open-source version under the Apache License 2.0. BasicAI offers private-cloud deployment starting at $6,600 a year, with customizable payment cycles and deployment options.

Verdict

Choose Potato if you need broad annotation coverage, model-assisted labeling, or agent evaluation and can operate a self-hosted tool. Its all-features free plan is compelling for that audience; look elsewhere if you need a managed cloud deployment.