# Protege

Protege is an Asset Manager based in New York, United States.

## Overview

- **Organization type:** Asset Manager
- **Headquarters:** New York, United States
- **Region:** North America
- **Address:** New York, NY, United States
- **Assets under management:** Undisclosed
- **Website:** withprotege.ai
- **LinkedIn:** https://www.linkedin.com/company/protege

## Regulatory record

- **Reports private funds:** No

## About

Be Heard. Get Discovered. See our official page at www.linkedin.com/company/join-protege

## Sectors

- AI/ML
- Digital Health
- Enterprise Software
- Media & Entertainment

## People

- Bobby Samuels — Co-Founder & CEO
- Travis May — Co-Founder & Chairman
- Engy Ziedan — Co-Founder & Chief Scientific Officer
- Richard Ho — Co-Founder & CTO

## Questions

### Who runs Protege, and what is their background?

Protege was co-founded by Bobby Samuels (CEO), Travis May (Chairman), Engy Ziedan (Chief Scientific Officer), and Richard Ho (CTO). The firm describes its leadership as combining experienced startup operators with depth across both data engineering and scientific research, though specific prior career details are not publicly detailed on the firm's materials.

### How does Protege source the data it provides to AI model builders?

Protege does not scrape data from the open web. It negotiates directly with data holders across industries — including hospitals, media archives, and industrial operators — and then curates, de-identifies, and structures that proprietary material into AI-ready datasets. The firm acts as an intermediary that aggregates supply from hundreds of sources and delivers it in formats tailored to each stage of model development.

### Does Protege simply license data, or does it also prepare and structure it for specific model training stages?

Protege is not a raw-data broker. Its 'DataLab' team provides domain-specific curation, de-identification, and quality checks so that datasets arrive matched to a builder's specific use case — pre-training corpora, supervised fine-tuning examples, or uncontaminated evaluation benchmarks — rather than as generic data feeds.

## Related profiles

- [Caliber Ventures](https://altss.com/profile/caliber-ventures)
- [LuminArx Capital Management](https://altss.com/profile/luminarx-capital-management)

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Last updated: 2026-06-03T20:00:00.000Z

Canonical page: https://altss.com/profile/protege

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