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Fraction AI

Category: AI Agents

A platform that empowers users to train and own their own AI models through a competitive, decentralized ecosystem. Fraction AI was founded in 2023. The company is led by Shashank Yadav. Based in San Francisco, CA, USA. Team size: 8. Total funding raised: $6 million. Latest round: Pre-seed, $6.0M, 2024-12, led by Spartan Group. Key investors include Borderless Capital, Anagram, Foresight Ventures, Karatage.

Founded
2023
Headquarters
San Francisco, CA, USA
Team size
8
Total funding
$6 million

Value proposition

Democratizes AI ownership by decentralizing data labeling and model training through competitive, self-improving ecosystem dynamics.

Products and solutions

Competitive AI agent platform, Crowdsourced data labeling system, FRAC token ecosystem for incentivization

Unique value

Decentralized, self-improving AI ecosystem where models evolve through competition and real-world feedback.

Target customer

Individuals and organizations seeking to develop specialized AI models

Industries served

Technology, Healthcare, Marketing

Technology advantage

Integrates human insights with AI agent competitions to generate and refine training data at scale.

How they differentiate

Enables users to train and own AI models via a decentralized, competition-based system, contrasting traditional centralized data annotation methods.

Main competitors

Dataforge, FastLabel

Key partnerships

Polygon (via advisor Sandeep Nailwal), NEAR Protocol (via advisor Illia Polosukhin)

Major milestones

Closed testnet launch with 60,000 users $6 million pre-seed funding round Plans for public testnet and mainnet launch in early 2025

Growth metrics

Over 60,000 users on the closed testnet

Market positioning

Positioned as a democratizing force in AI by leveraging decentralized technology and competitive innovation to disrupt traditional AI data labeling.

Geographic focus

Global, with a strong focus on the US market

About Shashank Yadav

IIT Delhi Computer Science graduate. Worked on core machine learning teams at Goldman Sachs and Microsoft, applying AI to quantitative trading in hedge funds. Previously worked at IBM and gained expertise in financial AI systems before founding Fraction AI to democratize AI ownership.

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