Humans& vs Snorkel AI

Side-by-side comparison of AI visibility scores, market position, and capabilities

Snorkel AI leads in AI visibility (81 vs 27)
Humans& logo

Humans&

EmergingArtificial Intelligence

Human-Centric AI Platform

Raised $480M seed at $4.48B valuation (Jan 2026). NVIDIA, Jeff Bezos, GV, Emerson Collective. Founded by ex-Anthropic, xAI, and Google researchers. AI amplifying human collaboration.

AI VisibilityBeta
Overall Score
D27
Category Rank
#1 of 1
AI Consensus
68%
Trend
up
Per Platform
ChatGPT
28
Perplexity
34
Gemini
33

About

Humans& is a human-centric AI company founded by some of the most decorated AI researchers of the current generation: Andi Peng (led Claude 3.5 and 4.5 at Anthropic), Eric Zelikman and Yuchen He (from Grok development at xAI), and Georges Harik (Google's 7th employee). The company raised $480 million in seed financing in January 2026 at a $4.48 billion valuation, backed by NVIDIA, Jeff Bezos, GV (Google Ventures), and Emerson Collective.

Full profile
Snorkel AI logo

Snorkel AI

LeaderAI & Machine Learning

General

Redwood City CA programmatic AI data labeling (private, $1B+ valuation, $135M Series C); Snorkel Flow LLM fine-tuning data pipelines, Stanford research spinout competing with Scale AI and Labelbox.

AI VisibilityBeta
Overall Score
A81
Category Rank
#33 of 1158
AI Consensus
85%
Trend
stable
Per Platform
ChatGPT
85
Perplexity
83
Gemini
83

About

Snorkel AI, Inc. is a Redwood City, California-based enterprise AI data development company — venture-backed private company (raised $135 million in Series C funding in 2022 at over $1 billion valuation) — providing the Snorkel Flow platform for programmatic data labeling and AI training data management, enabling data science and ML engineering teams to create, manage, and improve labeled training datasets using programmatic labeling functions (Labeling Functions) rather than manual human annotation at scale. Founded in 2019 by Alex Ratner and Christopher Ré (Stanford University AI Lab researchers who developed the original Snorkel research project and published the foundational "Data Programming" paper demonstrating that weak supervision and programmatic labeling could generate training data at 10-100x lower cost than traditional human annotation), Snorkel AI commercializes the academic breakthrough that AI training data quality and quantity — rather than model architecture complexity alone — determines AI system performance in enterprise applications. Snorkel Flow's core capability (enabling domain experts to write Python labeling functions that programmatically annotate training data based on rules, patterns, and weak signals) was adopted by major enterprises including Google, Apple, Stanford Hospital, and US intelligence agencies for NLP, computer vision, and multimodal AI data pipeline management. The company raised $135 million Series C led by Lightspeed Venture Partners, Greylock Partners, and Bain Capital Ventures to expand enterprise sales, add multi-modal data support (images, video, audio alongside text), and develop foundation model fine-tuning capabilities for large language model customization.

Full profile

AI Visibility Head-to-Head

27
Overall Score
81
#1
Category Rank
#33
68
AI Consensus
85
up
Trend
stable
28
ChatGPT
85
34
Perplexity
83
33
Gemini
83
21
Claude
89
27
Grok
85

Key Details

Category
Human-Centric AI Platform
General
Tier
Emerging
Leader
Entity Type
brand
brand

Capabilities & Ecosystem

Capabilities

Only Humans&
Human-Centric AI Platform

Integrations

Only Snorkel AI

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