Pendium
Asimov
Asimov
Visibility16
Vibe80
Businesses/Artificial Intelligence & Robotics/Asimov
Asimov
AI Visibility & Sentiment

Asimov

Asimov collects diverse real-world human activity data at scale to power the next generation of robotics AI. They capture egocentric video from everyday tasks across multiple continents, transforming it into clean, annotated datasets that teach robots to understand physical world interactions.

Active Monitoring
tryasimov.ai
Artificial Intelligence & RoboticsYC25-26
AI Visibility Score
16/100

Invisible

Sentiment Score
80/100
AI Perception

Summary

Asimov holds a highly specialized but narrow stronghold within the Claude ecosystem, capturing elite #1 rankings for robotics infrastructure queries while remaining completely absent from Google's AI Overviews. While the brand resonates strongly with Robotics Startup CTOs, its total invisibility to academic researchers and foundation model leads represents a critical disconnect from the broader AI development lifecycle.

Value Proposition

Solving robotics' data scarcity problem by collecting massive-scale, diverse human activity data from real environments across continents—not controlled labs—enabling robots to learn from the messy reality of how humans actually move through the physical world.

Overview

Asimov collects diverse real-world human activity data at scale to power the next generation of robotics AI. They capture egocentric video from everyday tasks across multiple continents, transforming it into clean, annotated datasets that teach robots to understand physical world interactions.

Mission

To bridge the massive gap between available robotics training data and the 16 hours of real-world physical activity generated by 8 billion people daily, enabling robots to truly understand the physical world.

Products & Services
Annotated robotics training datasetsEnd-to-end data collection pipelineEgocentric video capture with 3D body pose and depth mapsData collection hardware distributionPaid data collection opportunities for individuals
Agent Breakdown

AI Platforms

How often do different AI platforms reference Asimov?

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Conversation Analysis

Topics

What conversations is Asimov included in — or excluded from?

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Buyer Personas

Personas

Who does each AI platform recommend Asimov to, and when?

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Programmatic Testing

Sample Conversations

We programmatically analyze questions that real customers are asking to AI agents and chatbots, extract brand mentions and sentiment, analyze every response, and synthesize the data into an action plan to increase AI visibility.

ChatGPTChatGPTClaudeClaudeGeminiGeminiAI OverviewsAI Overviews
Training Embodied AI For Real World Tasks(2 queries)

“where can i find large scale egocentric video datasets with 3D body pose for training humanoid robots”

0/3 platforms mentioned

ClaudeClaude
1.EgoPose
2.EgoBody
3.Meta AI Research
4.Ego4D
5.Human3.6M

+3 more

GeminiGemini
1.Ego-Exo4D
2.Meta Aria
3.EgoBody
4.Microsoft HoloLens 2
5.Vicon

+6 more

AI OverviewsAI Overviews
1.Ego-Exo4D
2.EgoDex
3.HOT3D
4.Project Aria
5.Quest 3

+7 more

“best ways to get diverse human activity data for embodied ai without using a lab”

0/3 platforms mentioned

ClaudeClaude
1.Aria Research Kit
2.GoPro
3.GoPro Hero 12
4.RealSense D455
5.Luxonis OAK

+9 more

GeminiGemini
1.Ego4D
2.Ego-Exo4D
3.EPIC-KITCHENS-100
4.Project Aria
5.Scale AI

+14 more

AI OverviewsAI Overviews
1.Moments in Time
2.Kinetics-700
3.EgoK360
4.ProcTHOR
5.Objaverse

+12 more

Building A Data Collection Infrastructure(1 query)

“help me build a tech stack for a robotics data collection pipeline”

0/4 platforms mentioned

ChatGPTChatGPT
1.NVIDIA
2.Jetson Orin
3.Orin NX
4.AGX Xavier
5.Intel NUC

+81 more

ClaudeClaude
1.ROS 2
2.gRPC
3.Apache Kafka
4.MQTT
5.MinIO

+36 more

GeminiGemini
1.ROS 2
2.MCAP
3.Zenoh
4.AWS IoT Greengrass
5.Resilio Connect

+14 more

AI OverviewsAI Overviews
1.Andreessen Horowitz
2.Foxglove.dev
3.ROS 2
4.MCAP
5.Foxglove

+24 more

Paid Data Collection Opportunities(1 query)

“how can i get paid to record myself doing chores for ai research”

0/4 platforms mentioned

ChatGPTChatGPT
1.Appen
2.TELUS International
3.Lionbridge AI
4.Scale AI
5.Amazon Mechanical Turk

+18 more

ClaudeClaude
1.Scale AI
2.Playment
3.Appen
4.Lionbridge
5.Boston Dynamics

+1 more

GeminiGemini
1.Tesla
2.Appen
3.TELUS International
4.Lionbridge AI
5.Clickworker

+12 more

AI OverviewsAI Overviews

No brands listed

Evaluating Robotics Data Providers(1 query)

“most trusted robotics training data providers for frontier ai models”

0/4 platforms mentioned

ChatGPTChatGPT
1.Scale AI
2.Labelbox
3.Appen
4.iMerit
5.Alegion

+37 more

ClaudeClaude
1.Scale AI
2.Labelbox
3.Argon Robotics
4.RoboTurk
5.CloudFactory

+3 more

GeminiGemini
1.Scale AI
2.Scale Robotics
3.Labelbox
4.Invisible Technologies
5.NVIDIA

+15 more

AI OverviewsAI Overviews
1.Scale AI
2.Turing
3.Sensei
4.iMerit
5.Labelbox

+5 more

Analysis

Key Insights

What AI visibility analysis reveals about this brand

Strength

Exceptional performance within Claude, achieving #1 rankings for specialized queries related to embodied AI training and infrastructure building.

Strength

High resonance with the Robotics Startup CTO persona, achieving a 60% mention rate which indicates strong relevance for hardware-focused decision makers.

Strength

Positive sentiment across all mentions, suggesting that when the brand is surfaced, the AI models characterize its contributions favorably.

Gap

Zero visibility in AI Overviews, a critical failure for capturing top-of-funnel search intent and broad industry awareness.

Gap

Complete lack of presence for the University Lab PI and Foundation Model Research Lead personas, ceding the academic and core research sectors to competitors like Ego4D and Scale AI.

Gap

Failure to appear in high-intent queries regarding 'paid data collection' and 'trusted data providers,' leaving the field open for Appen and Scale AI to dominate the vendor landscape.

Opportunity

Translate the high-ranking Claude performance into ChatGPT and Gemini by aligning technical documentation with their specific indexing patterns.

Opportunity

Target the 'Ego4D' and 'Ego-Exo4D' audience by positioning Asimov as the commercial-grade alternative for large-scale egocentric video datasets.

Opportunity

Develop specific content addressing 'data collection infrastructure' to move from a #51 position in ChatGPT to the top 10, mirroring the success seen in Claude.

Technical Health

Site Health for AI Visibility

How well Asimov's website is optimized for AI agent discovery and comprehension.

83/100
12 passed 5 warnings 1 issues
Audited 2/27/2026
Crawlability83

Can AI bots find your pages?

Technical96

SSL, mobile, doctype basics

On-Page SEO91

Titles, descriptions, headings

Content Quality47

Word count, depth, freshness

Schema Markup85

Structured data for AI comprehension

Social & OG82

Open Graph, Twitter cards

AI Readability60

How well AI can parse your content

Critical Issues

!

Content is too thin

Expand your content to at least 300-500 words with valuable information.

Warnings

!

No robots.txt file found

Create a robots.txt file at your domain root. Optional but recommended.

!

2 render-blocking resource(s) detected

Consider deferring or async-loading non-critical scripts and stylesheets.

!

Title is too short (6 characters)

Expand the title to 50-60 characters with descriptive keywords.

!

Few headings on page

Add more H2 and H3 headings to organize content into sections.

!

Few internal links on this page

Add more internal links to related pages on your site.

+ 1 more warnings

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Brand Identity

Brand Voice & Style

How AI perceives Asimov's communication style and personality

Asimov communicates with technical precision balanced by accessible explanations, positioning themselves as serious problem-solvers tackling a fundamental challenge in robotics. Their voice is direct and confident, backed by data-driven arguments about the scale gap in robotics training data. They maintain a startup energy—ambitious yet practical—while speaking to both technical audiences and everyday people who might contribute data. The tone is professional but not corporate, with a clear mission-driven purpose.

Core Tone Traits

Technical yet Accessible

Explains complex robotics and AI concepts in clear, understandable terms without dumbing down the science

Mission-Driven & Purposeful

Communicates with conviction about solving a fundamental problem in robotics AI development

Direct & Confident

Makes bold claims backed by concrete data points and clear value propositions

Practical & Solutions-Oriented

Focuses on tangible outcomes and real-world applications rather than hype

Competitive Landscape

Related Ecosystem

Related products and services that AI mentions in conversations alongside or instead of Asimov

1Scale AI21 mentions
2Appen13 mentions
3Ego4D12 mentions
4Labelbox11 mentions
5Ego-Exo4D10 mentions
6Project Aria9 mentions
7EgoBody8 mentions
8Figure AI8 mentions
9Weights & Biases6 mentions
10TELUS International6 mentions
11Asimov6 mentions
Source Intelligence

Citations

Sources that AI assistants cite. Getting featured here improves visibility.

ego-exo4d-data.org

http://ego-exo4d-data.org/

Referenced in 1 query

Review
egobody.is.tue.mpg.de

http://egobody.is.tue.mpg.de/

Referenced in 1 query

Review
about.facebook.com/realitylabs/projectaria/datasets

https://about.facebook.com/realitylabs/projectaria/datasets

Referenced in 1 query

Pitch Story
amass.is.tue.mpg.de

http://amass.is.tue.mpg.de/

Referenced in 1 query

Review
ego4d-data.org

http://ego4d-data.org/

Referenced in 1 query

Review
hoi4d.github.io

https://hoi4d.github.io/

Referenced in 1 query

Pitch Story
EgoDex: Learning Dexterous Manipulation from Large-Scale ...

https://machinelearning.apple.com/research/egodex-learning-dexterous-manipulation

Referenced in 1 query

Review
An Egocentric Dataset for 3D Hand and Object Tracking

https://arxiv.org/html/2406.09598v1

Referenced in 1 query

Review
EgoBody: Human Body Shape and Motion of Interacting ...

https://sanweiliti.github.io/egobody/egobody.html

Referenced in 1 query

Pitch Story
Robotize Human Videos to Generate Humanoid Videos at Scale

https://arxiv.org/html/2512.04537v1

Referenced in 1 query

Review
Introducing Ego-Exo4D: A foundational dataset for research ...

https://ai.meta.com/blog/ego-exo4d-video-learning-perception/

Referenced in 1 query

Review
EgoScale - Research at NVIDIA

https://research.nvidia.com/labs/gear/egoscale/

Referenced in 1 query

Review
Content Engineering

Recommended Actions

!

Execute a technical SEO and content audit specifically targeting Google's AI Overviews to break the current 0% visibility barrier.

AI Overviews are becoming a primary discovery layer; being invisible here ensures competitors like Scale AI capture all mainstream market interest.

Impact: High
!

Develop an academic outreach and 'Open Data' content strategy to win over the University Lab PI persona.

Asimov is currently a ghost in the research community, while open datasets like Ego4D are cited as industry standards by all major LLMs.

Impact: High
~

Create comparison-based technical whitepapers focusing on 'Frontier AI Training' and 'Frontier Data Providers'.

Competitors like Appen and Labelbox are winning on 'trust' and 'frontier' queries; Asimov needs to explicitly claim these keywords to be considered in vendor shortlists.

Impact: Medium
~

Reverse-engineer the documentation structure that led to the #1 ranking in Claude and replicate it across all product pages.

Asimov has clearly cracked the code for Claude's reasoning; standardizing this approach will help improve the poor average position (#51) currently seen in ChatGPT.

Impact: Medium

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Data generated by Pendium.ai AI visibility scanning. Last scanned February 27, 2026.

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