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📚Complete Guide

Protégé Tutorial: Get Started in 5 Minutes [2026]

Master Protégé with our step-by-step tutorial, detailed feature walkthrough, and expert tips.

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🔍 Protégé Features Deep Dive

Explore the key features that make Protégé powerful for coding agents workflows.

Full AI Lifecycle Data Coverage

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Healthcare AI Evaluation Datasets and Benchmarks

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Two-Sided Data Marketplace with Rights Protection

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Multi-Modal Domain Specialization

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Consultative Sourcing Model

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❓ Frequently Asked Questions

What types of data does Protégé provide?

Protégé sources real-world, proprietary data across five primary domains: healthcare (including multimodal patient journey data, clinical documentation, and medical imaging), video, audio and speech, spatial and physical intelligence (including motion capture), and other industry-specific verticals. The platform supports all four stages of the AI development lifecycle, from massive diverse pre-training datasets to narrowly curated fine-tuning data and uncontaminated benchmark datasets. Unlike public scrape-based corpora, Protégé focuses specifically on private and proprietary data that is not otherwise available.

How much does Protégé cost?

Protégé uses enterprise pricing that is not published on its website, meaning all engagements require direct contact with their sales and partnerships team. Pricing is presumably tailored to the volume, modality, and exclusivity of the data being licensed, as well as the scope of the consultative work needed to source and prepare it. This model is consistent with other premium AI data platforms targeting frontier labs and enterprise customers, though it makes the platform inaccessible to smaller teams and individual researchers. Prospective buyers should expect a custom quote process rather than a public pricing page.

Who founded Protégé and how is it funded?

Protégé operates under the corporate name Protege Health, Inc. and is headquartered at 169 Madison Ave, New York, NY. The company announced a $25 million Series A in February 2026 to expand its AI training data platform, followed by a $30 million Series A extension led by Andreessen Horowitz (a16z), bringing total Series A funding to approximately $55 million. The extension was driven by rapid adoption across healthcare, media, audio, motion capture, and other verticals as AI companies increasingly need high-quality, non-public data.

How does Protégé differ from Scale AI or other data labeling platforms?

Based on our analysis of 870+ AI tools, Protégé differs from labeling-first platforms like Scale AI, Labelbox, and SuperAnnotate by focusing on data sourcing rather than annotation of existing data. Its core value proposition is connecting model builders with genuinely proprietary, non-public data held by hospitals, studios, and enterprises, with rights and provenance protections built in. Customer testimonials describe Protégé as a hands-on internal partner that helps identify the right data for specific problems, rather than a self-serve data catalog. This makes it more comparable to a specialized data brokerage than to a labeling tools vendor.

Can data providers monetize their datasets through Protégé?

Yes — Protégé runs a dedicated 'For Data Providers' program that allows organizations holding proprietary datasets or content to generate revenue by licensing that data to AI builders. The platform emphasizes maintaining clear rights protections and provenance tracking throughout the exchange, which is particularly important for regulated domains like healthcare. Data providers can participate across the same five domains the platform serves: healthcare, video, audio and speech, spatial and physical intelligence, and other domains. This two-sided marketplace model is one of the platform's distinguishing features compared to pure-buy-side data vendors.

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Tutorial updated March 2026