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10x Science
10x Science
Visibility0
Vibe83
Businesses/Biotechnology Software/10x Science
10x Science
AI Visibility & Sentiment

10x Science

10x Science develops AI-native software for next-generation protein characterization, enabling scientists to molecularly analyze proteins at scale in real time. The platform was developed by researchers from Stanford, MIT, UC Berkeley, UCSF, and UW Madison, and is backed by Y Combinator.

Active Monitoring
10xscience.com
Biotechnology SoftwareYC25-26
AI Visibility Score
0/100

Invisible

Sentiment Score
83/100
Score by Priority

How often this business is recommended to users across different types of conversations — from direct product queries to broader open-ended conversations where AI could recommend this company's products and services

core
0
adjacent
0
OverviewLandscapeInsights & ActionsConversationsCitationsBrand Voice

Is this your business?

AI Perception

Key Takeaways

How AI platforms collectively perceive and describe 10x Science today.

10x Science currently operates in a total discovery vacuum, remaining completely invisible during high-intent searches for proteomics and peptide mapping while competitors like Protein Metrics and MaxQuant dominate the conversational landscape. Although the brand is recognized in direct 'vibe checks' by Claude and AI Overviews, it is entirely absent from the critical decision-making workflows of facility managers and infrastructure architects.

Working in your favor

Retains basic brand identity and factual awareness within Claude and AI Overviews during direct brand-specific queries

Exists within the training data of major LLMs, allowing for accurate identification when prompted specifically about the company

Gaps to close

Total absence in 'Next-Gen Omics' and 'vendor-neutral' software queries where competitors like Waters and Bruker are frequently recommended

Zero visibility among the Bioinformatics Infrastructure Architect and Pharmaceutical Protein Characterization Lead personas

Failure to appear in any top-down proteomics or proteoform resolution workflow recommendations despite these being core industry challenges

Opportunities

Establish a 'vendor-neutral' authority play to disrupt the dominance of hardware-aligned software like Thermo and Waters

Capture the 'de novo protein sequencing' search intent where current AI recommendations are highly concentrated among a few legacy players

Leverage the existing recognition in AI Overviews to bridge the gap into category-specific queries through structured technical content

Highest-Impact Actions
1

Optimize technical whitepapers for 'top-down proteoform resolution' and 'peptide mapping' keywords.

10x Science is currently invisible in these high-intent research queries while competitors are cited 15+ times.

2

Develop targeted content assets for the 'Bioinformatics Infrastructure Architect' persona.

This persona showed a 0% mention rate, representing a massive missed opportunity to influence technical gatekeepers.

3

Pursue inclusion in third-party 'Best Proteomics Software' comparison articles and benchmarks.

AI models heavily weight external citations; competitors like MaxQuant and FragPipe are winning because they are mentioned across various trusted bioinformatics platforms.

Value Proposition

The first AI/ML-native omics software that delivers 10x faster processing, intelligently resolves complex PTMs, and provides vendor-neutral integration for protein characterization workflows.

Overview

10x Science develops AI-native software for next-generation protein characterization, enabling scientists to molecularly analyze proteins at scale in real time. The platform was developed by researchers from Stanford, MIT, UC Berkeley, UCSF, and UW Madison, and is backed by Y Combinator.

Mission

Democratize how scientists analyze complex protein data in real time using frontier AI software.

Products & Services
AI-native protein characterization platformTop-down proteomics analysisPeptide mapping for protein therapeuticsProteoform resolution and PTM analysisDe novo protein sequencing
Current State

Visibility Landscape

A high-level view of how 10x Science performs across AI platforms, broken down by strategic priority level — from core brand queries to growth opportunities.

ChatGPTChatGPT
ClaudeClaude
GeminiGemini
AI OverviewsAI Overviews

Reputation1q

Brand recognition & direct queries

0
97
70
97
“What do you know about 10x Science? What do they do and what's their reputation?”
No
#1
Yes
#1

Core4q

Product/service category queries

0
0
0
0
“best tools for peptide mapping in protein therapeutics, looking for something faster than biopharma finder”
No
No
No
No
“find me a vendor-neutral software for proteomics that supports data from both thermo and bruker”
No
No
No
No
“most trusted protein characterization software for high-throughput labs”
No
No
No
No
“recommend some software for de novo protein sequencing that actually works with complex PTMs”
No
No
No
No

Growth Areas1q

Adjacent, aspirational & visionary

0
0
0
0
“how can i get better proteoform resolution from my top-down mass spec data”
No
No
No
No
ChatGPT
Claude
Gemini
AI Overviews

“What do you know about 10x Science? What do they do and what's their reputation?”

ChatGPTNo
Claude#1
GeminiYes
AI Overviews#1

“best tools for peptide mapping in protein therapeutics, looking for something faster than biopharma finder”

ChatGPTNo
ClaudeNo
GeminiNo
AI OverviewsNo

“find me a vendor-neutral software for proteomics that supports data from both thermo and bruker”

ChatGPTNo
ClaudeNo
GeminiNo
AI OverviewsNo

“most trusted protein characterization software for high-throughput labs”

ChatGPTNo
ClaudeNo
GeminiNo
AI OverviewsNo

“recommend some software for de novo protein sequencing that actually works with complex PTMs”

ChatGPTNo
ClaudeNo
GeminiNo
AI OverviewsNo

“how can i get better proteoform resolution from my top-down mass spec data”

ChatGPTNo
ClaudeNo
GeminiNo
AI OverviewsNo
Competitive Landscape
1
Protein Metrics
19 mentions
2
MaxQuant
19 mentions
3
Thermo
18 mentions
4
Waters
18 mentions
5
Bruker
18 mentions
6
Orbitrap
18 mentions
7
FragPipe
16 mentions
8
MSFragger
15 mentions
9
PEAKS Studio
14 mentions
10
Byonic
13 mentions
11
10x Science
0 mentions
Analysis

Insights & Recommended Actions

What's working, what's not, and specific steps to improve 10x Science's AI visibility.

Key Findings

Strength

Retains basic brand identity and factual awareness within Claude and AI Overviews during direct brand-specific queries

Strength

Exists within the training data of major LLMs, allowing for accurate identification when prompted specifically about the company

Gap

Total absence in 'Next-Gen Omics' and 'vendor-neutral' software queries where competitors like Waters and Bruker are frequently recommended

Recommended Actions

1

Optimize technical whitepapers for 'top-down proteoform resolution' and 'peptide mapping' keywords.

10x Science is currently invisible in these high-intent research queries while competitors are cited 15+ times.

2

Develop targeted content assets for the 'Bioinformatics Infrastructure Architect' persona.

This persona showed a 0% mention rate, representing a massive missed opportunity to influence technical gatekeepers.

3

Pursue inclusion in third-party 'Best Proteomics Software' comparison articles and benchmarks.

AI models heavily weight external citations; competitors like MaxQuant and FragPipe are winning because they are mentioned across various trusted bioinformatics platforms.

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
Advanced Proteomics Research & Workflow Optimization(2 queries)

“how can i get better proteoform resolution from my top-down mass spec data”

0/4 platforms mentioned

Adjacent
ChatGPTChatGPT
1.Thermo
2.Zeba
3.Pierce
4.P6 spin columns
5.RapiGest

+31 more

ClaudeClaude
1.Orbitrap Fusion Lumos
2.Q-Exactive HF-X
3.ProSight
4.MASH Suite
5.UniDec

+1 more

GeminiGemini
1.GELFREE 8100
2.Expedeon
3.Abcam
4.Thermo Fisher MAbPac
5.Waters BioResolve

+13 more

AI OverviewsAI Overviews
1.Azo
2.PubMed Central
3.FLASHIda
4.Biocompare
5.TopFD

+5 more

“recommend some software for de novo protein sequencing that actually works with complex PTMs”

0/4 platforms mentioned

Core
The Multi-Vendor Core Facility Manager · Core Facility Director
ChatGPTChatGPT
1.PEAKS Studio
2.Bioinformatics Solutions Inc.
3.Thermo
4.Bruker
5.Waters

+27 more

ClaudeClaude
1.PEAKS Studio
2.Bioinformatics Solutions Inc.
3.MaxQuant
4.FragPipe
5.University of Michigan

+9 more

GeminiGemini
1.Orbitrap
2.timsTOF
3.Waters
4.PEAKS Studio
5.PEAKS Online

+23 more

AI OverviewsAI Overviews
1.PEAKS Studio
2.PEAKS AB
3.PEAKS PTM
4.Unimod
5.SPIDER

+8 more

Source Intelligence

Citations

The sources AI platforms cite when recommending this brand. Pendium reverse-engineers what's already proven to be catnip to AI agents, then engineers content that fills gaps and helps agents do their job — which means more citations for you.

Progress in Top-Down Proteomics and the Analysis of Proteoforms

pmc.ncbi.nlm.nih.gov

Gov1 ref

Software - Consortium for Top-Down Proteomics

ctdp.org

Web1 ref

TopFD: A Proteoform Feature Detection Tool for Top–Down ...

pubs.acs.org

Web1 ref

Spectral averaging with outlier rejection algorithms to increase ...

pmc.ncbi.nlm.nih.gov

Gov1 ref

TopPIC: a software tool for top-down mass spectrometry ...

academic.oup.com

Web1 ref

Novel Strategies to Address the Challenges in Top-Down ...

pmc.ncbi.nlm.nih.gov

Gov1 ref

mass graph-based approach for the identification of modified ...

academic.oup.com

Web1 ref

Get the Big Picture with Top-Down Proteomics | Biocompare

biocompare.com

Web1 ref

FLASHIda enables intelligent data acquisition for top ... - Nature

nature.com

Web1 ref

Mesh fragmentation improves dissociation efficiency in top-down ...

pmc.ncbi.nlm.nih.gov

Gov1 ref

Top-down Mass Spectrometry (MS)-based proteomics - Ying Ge

labs.wisc.edu

Edu1 ref

Identification of proteoforms by top‐down proteomics using ...

analyticalsciencejournals.onlinelibrary.wiley.com

Web1 ref

Top‐Down Proteomics: Why and When? - PMC - PubMed Central - NIH

pmc.ncbi.nlm.nih.gov

Gov1 ref

MSFragger / FragPipe

fragpipe.nesvilab.org

Web1 ref

DIA-NN

github.com

Code1 ref
Brand Identity

Brand Voice & Style

How AI perceives 10x Science's communication style and personality

10x Science communicates with scientific precision and technical authority while remaining accessible to researchers across experience levels. The brand voice balances cutting-edge innovation with practical utility, emphasizing speed, accuracy, and democratization of complex analysis. The tone is confident but not arrogant, using clear language to explain sophisticated AI capabilities without oversimplifying the science.

Core Tone Traits

Scientifically Authoritative

Speaks with deep domain expertise in proteomics and mass spectrometry

Innovation-Forward

Emphasizes AI/ML capabilities and next-generation approaches

Accessible & Clear

Makes complex technical concepts understandable without dumbing down

Researcher-Centric

Focuses on solving real pain points scientists face daily

Visual Identity

Primary

#A855ED

Secondary

#C084FC

Accent

#9333EA

Background

#FFFFFF

Foreground

#111111

Backing

Investors

Y
Y Combinator

Engineer content that makes AI agents recommend you

Pendium analyzes how AI platforms perceive your brand, reverse-engineers what they already cite, and continuously publishes content designed to fill gaps and earn more mentions — on autopilot, with you in the loop.

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

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Frequently asked questions

Don't see your question? Book a demo and we'll walk you through it.

10x Science develops AI-native software for next-generation protein characterization, enabling scientists to molecularly analyze proteins at scale in real time. The platform was developed by researchers from Stanford, MIT, UC Berkeley, UCSF, and UW Madison, and is backed by Y Combinator.

The first AI/ML-native omics software that delivers 10x faster processing, intelligently resolves complex PTMs, and provides vendor-neutral integration for protein characterization workflows.

AI Visibility Score

10x Science has an AI visibility score of 0/100, rated as invisible. This score reflects how often and how prominently 10x Science appears in responses from AI assistants like ChatGPT, Claude, and Gemini.

AI Perception Summary

10x Science currently operates in a total discovery vacuum, remaining completely invisible during high-intent searches for proteomics and peptide mapping while competitors like Protein Metrics and MaxQuant dominate the conversational landscape. Although the brand is recognized in direct 'vibe checks' by Claude and AI Overviews, it is entirely absent from the critical decision-making workflows of facility managers and infrastructure architects.

Strengths

  • Retains basic brand identity and factual awareness within Claude and AI Overviews during direct brand-specific queries
  • Exists within the training data of major LLMs, allowing for accurate identification when prompted specifically about the company

Visibility Gaps

  • Total absence in 'Next-Gen Omics' and 'vendor-neutral' software queries where competitors like Waters and Bruker are frequently recommended
  • Zero visibility among the Bioinformatics Infrastructure Architect and Pharmaceutical Protein Characterization Lead personas
  • Failure to appear in any top-down proteomics or proteoform resolution workflow recommendations despite these being core industry challenges

Competitors in AI Recommendations

  • Protein Metrics: 19 mentions
  • MaxQuant: 19 mentions
  • Thermo: 18 mentions
  • Waters: 18 mentions
  • Bruker: 18 mentions
  • Orbitrap: 18 mentions
  • FragPipe: 16 mentions
  • MSFragger: 15 mentions
  • PEAKS Studio: 14 mentions
  • Byonic: 13 mentions
  • OpenMS: 13 mentions
  • Spectronaut: 12 mentions
  • Skyline: 12 mentions
  • BioPharma Finder: 12 mentions
  • Biognosys: 11 mentions

Categories: Biotechnology Software

Tags: YC25-26