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Mantis
Mantis
Visibility22
Vibe81
Businesses/Healthcare Technology/Mantis
Mantis
AI Visibility & Sentiment

Mantis

Mantis is a data platform for life sciences organizations that transforms complex biological, clinical, and operational data into reusable, canonical datasets. The platform integrates with existing systems like EDC, CTMS, and lab vendors to enable cross-study analytics, AI readiness, and real-time performance insights.

Active Monitoring
mantisbiotech.com
Healthcare TechnologyYC25-26
AI Visibility Score
22/100

Low

Sentiment Score
81/100
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
22
OverviewLandscapeInsights & ActionsConversationsCitationsBrand Voice

Is this your business?

AI Perception

Key Takeaways

How AI platforms collectively perceive and describe Mantis today.

Mantis is currently a phantom leader in the clinical data space, securing elite top-three rankings in Claude and Gemini for infrastructure queries while suffering a total blackout in Google AI Overviews and ChatGPT. This stark divide reveals that while LLMs recognize Mantis’s technical superiority in handling data fragmentation, the brand is failing to register in the broader search-generative ecosystem where legacy giants like Medidata and Veeva still dominate the narrative.

Working in your favor

Exceptional performance in Claude and Gemini for 'Modernizing Clinical Data Infrastructure' queries, reaching as high as position #2.

Strong resonance with Strategic Clinical Operations Leaders, achieving a 58% mention rate and high positive sentiment.

High technical authority in Claude specifically regarding 'data fragmentation in clinical trials,' where it consistently outperforms broader competitors.

Gaps to close

Total lack of visibility (0%) in Google AI Overviews across all tested queries, a critical failure in the search-generative experience.

Complete absence from the 'Modern alternatives to Veeva/Medidata' conversation, allowing legacy vendors to maintain their market capture.

Negligible presence in ChatGPT, where its average position of 22.0 effectively makes the brand undiscoverable for mainstream AI users.

Opportunities

Own the 'AI-Ready Data Strategy' category where visibility is currently low, positioning Mantis as the essential foundation for AI-driven trials.

Leverage current mixed sentiment among Biotech Startup Founders by producing targeted 'founder-first' content that addresses the cost and scale barriers of legacy systems.

Capitalize on Claude’s high preference for Mantis by seeding more technical documentation to convert 'mixed' sentiment into 'positive' authority.

Highest-Impact Actions
1

Execute an 'AI-Ready' Content Blitz

Mantis was only mentioned once for 'AI-ready data strategy' (Gemini #3). Dominating this specific query across all platforms is the fastest path to being seen as a future-proof alternative to Veeva.

2

Address the AIOverviews Blackout

Zero visibility in Google’s SGE suggests a lack of structured, schema-rich technical content that Google's crawlers can synthesize. Immediate optimization of the 'how-to' clinical integration pages is required.

3

Direct Competitive Positioning Content

Since Mantis is currently excluded from 'modern alternative' queries, the brand must publish explicit comparison and migration guides (e.g., 'Transitioning from Veeva Vault to Modern Infrastructure') to trigger these associations in LLM training sets.

Value Proposition

Mantis solves the data fragmentation problem in life sciences by creating domain-aware, reusable datasets that encode biological and clinical meaning directly into the data, enabling teams to run cross-study analytics without rebuilding pipelines.

Overview

Mantis is a data platform for life sciences organizations that transforms complex biological, clinical, and operational data into reusable, canonical datasets. The platform integrates with existing systems like EDC, CTMS, and lab vendors to enable cross-study analytics, AI readiness, and real-time performance insights.

Mission

Making customers' lives easier with the most intuitive analytics tool for life sciences data.

Products & Services
Canonical biomedical and clinical datasetsCross-system data integration platformReal-time clinical trial performance analyticsAI-ready data preparationCustom integrations for legacy and vendor platforms
Current State

Visibility Landscape

A high-level view of how Mantis 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

70
70
70
70
“What do you know about Mantis? What do they do and what's their reputation?”
Yes
Yes
Yes
Yes

Core5q

Product/service category queries

18
52
64
0
“how to integrate clinical data from different systems like EDC and CTMS into one place”
#23
#2
#10
No
“how do I make our clinical trial data AI-ready”
No
No
#3
No
“how to get real-time performance analytics for my clinical trials”
No
No
#15
No
“modern alternatives to big clinical data vendors like Veeva or Medidata”
No
No
No
No
“best ways to handle data fragmentation in clinical trials, specific platforms to look at”
—
#2
#2
No

Growth Areas

Adjacent, aspirational & visionary

—
—
—
—
ChatGPT
Claude
Gemini
AI Overviews

“What do you know about Mantis? What do they do and what's their reputation?”

ChatGPTYes
ClaudeYes
GeminiYes
AI OverviewsYes

“how to integrate clinical data from different systems like EDC and CTMS into one place”

ChatGPT#23
Claude#2
Gemini#10
AI OverviewsNo

“how do I make our clinical trial data AI-ready”

ChatGPTNo
ClaudeNo
Gemini#3
AI OverviewsNo

“how to get real-time performance analytics for my clinical trials”

ChatGPTNo
ClaudeNo
Gemini#15
AI OverviewsNo

“modern alternatives to big clinical data vendors like Veeva or Medidata”

ChatGPTNo
ClaudeNo
GeminiNo
AI OverviewsNo

“best ways to handle data fragmentation in clinical trials, specific platforms to look at”

ChatGPT—
Claude#2
Gemini#2
AI OverviewsNo
Competitive Landscape
1
Snowflake
20 mentions
2
Medidata Rave
20 mentions
3
Medidata
20 mentions
4
Veeva
19 mentions
5
Databricks
14 mentions
6
Mantis
14 mentions
7
Veeva Vault
13 mentions
8
Tableau
12 mentions
9
dbt
11 mentions
10
Saama Technologies
10 mentions
11
Viedoc
9 mentions
Analysis

Insights & Recommended Actions

What's working, what's not, and specific steps to improve Mantis's AI visibility.

Key Findings

Strength

Exceptional performance in Claude and Gemini for 'Modernizing Clinical Data Infrastructure' queries, reaching as high as position #2.

Strength

Strong resonance with Strategic Clinical Operations Leaders, achieving a 58% mention rate and high positive sentiment.

Strength

High technical authority in Claude specifically regarding 'data fragmentation in clinical trials,' where it consistently outperforms broader competitors.

Recommended Actions

1

Execute an 'AI-Ready' Content Blitz

Mantis was only mentioned once for 'AI-ready data strategy' (Gemini #3). Dominating this specific query across all platforms is the fastest path to being seen as a future-proof alternative to Veeva.

2

Address the AIOverviews Blackout

Zero visibility in Google’s SGE suggests a lack of structured, schema-rich technical content that Google's crawlers can synthesize. Immediate optimization of the 'how-to' clinical integration pages is required.

3

Direct Competitive Positioning Content

Since Mantis is currently excluded from 'modern alternative' queries, the brand must publish explicit comparison and migration guides (e.g., 'Transitioning from Veeva Vault to Modern Infrastructure') to trigger these associations in LLM training sets.

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
Modernizing Clinical Data Infrastructure(2 queries)

“how to integrate clinical data from different systems like EDC and CTMS into one place”

0/4 platforms mentioned

Core
ChatGPTChatGPT
1.Mulesoft
2.Dell Boomi
3.Talend
4.Snowflake
5.BigQuery

+34 more

ClaudeClaude
1.Medidata Rave
2.Oracle InForm
3.Medidata CTMS
4.Veeva Vault
5.Informatica

+11 more

GeminiGemini
1.Veeva Vault Clinical
2.Vault EDC
3.Vault CTMS
4.Medidata Rave (DDS)
5.Medidata Clinical Cloud

+13 more

AI OverviewsAI Overviews
1.Viedoc
2.Medidata Clinical Cloud
3.Veeva Vault
4.Clinion
5.SimpleTrials

+1 more

“best ways to handle data fragmentation in clinical trials, specific platforms to look at”

2/3 platforms mentioned

Core
The Technical Bio-Data Architect · Senior Data Architect
ClaudeClaude
1.Medidata Rave
2.Oracle InForm
3.Snowflake
4.Iceberg Tables
5.Databricks
8.Mantis

+3 more

GeminiGemini
1.Databricks
2.Delta Lake
3.Unity Catalog
4.Delta Sharing
5.MLflow
11.Mantis

+6 more

AI OverviewsAI Overviews
1.Medidata Solutions
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.

How to Integrate CTMS with EDC - Flex Databases

flexdatabases.com

Web1 ref

Modernizing Clinical Trials: The Role of eTMF, CTMS, and EDC ...

credevo.com

Web1 ref

CTMS & EDC Integration — SimpleTrials - Clinical Trial ...

simpletrials.com

Web1 ref

CTMS and EDC Integration in DCTs: Key Benefits and Tips

cdconnect.net

Web1 ref

What Electronic data capture systems are most commonly ...

reddit.com

Forum1 ref

CTMS vs. EDC: understanding the differences and benefits for ...

viedoc.com

Web1 ref

Building Integrations with Disparate Systems in the Clinical Trial ...

linkedin.com

Social1 ref

Electronic Clinical Trial Management Systems: The Basics ...

socra.org

Web1 ref

Best Life Science E-Clinical Systems Reviews 2026 - Gartner

gartner.com

Web1 ref

Clinical Data Management: Data Integration vs. Data ...

precisionformedicine.com

Web1 ref

Integrating Clinical Data: Overcoming Challenges and Maximizing ...

blog.cloudbyz.com

Web1 ref

5 Tips for a Successful Integration of CTMS with EDC - AQ Trials

aq-trials.com

Web1 ref

Prepare Clinical Data for AI: Startup Guide - Edenlab

edenlab.io

Web1 ref

How to Make Pharma Data AI-Ready for Better Outcomes

tekinvaderz.com

Web1 ref

How to Analyze and Integrate Clinical Trials Data Effectively?

elucidata.io

Web1 ref
Brand Identity

Brand Voice & Style

How AI perceives Mantis's communication style and personality

Mantis communicates with technical precision and domain expertise, speaking directly to the pain points of life sciences data professionals. The tone is confident and authoritative without being condescending, using industry-specific terminology that resonates with their technical audience. The brand balances sophisticated technical concepts with clear, outcome-focused messaging that emphasizes practical value over abstract features.

Core Tone Traits

Technically Authoritative

Uses precise life sciences and data terminology that demonstrates deep domain expertise

Problem-Solution Oriented

Leads with pain points and follows with clear, practical solutions

Confidently Understated

Makes bold claims backed by specifics without hyperbole or marketing fluff

Customer-Centric

Focuses on customer outcomes like shortened timelines and reduced complexity

Visual Identity

Primary

#FFFFFF

Secondary

#4A9FD4

Accent

#F5F5F5

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.

Mantis is a data platform for life sciences organizations that transforms complex biological, clinical, and operational data into reusable, canonical datasets. The platform integrates with existing systems like EDC, CTMS, and lab vendors to enable cross-study analytics, AI readiness, and real-time performance insights.

Mantis solves the data fragmentation problem in life sciences by creating domain-aware, reusable datasets that encode biological and clinical meaning directly into the data, enabling teams to run cross-study analytics without rebuilding pipelines.

AI Visibility Score

Mantis has an AI visibility score of 21/100, rated as low. This score reflects how often and how prominently Mantis appears in responses from AI assistants like ChatGPT, Claude, and Gemini.

AI Perception Summary

Mantis is currently a phantom leader in the clinical data space, securing elite top-three rankings in Claude and Gemini for infrastructure queries while suffering a total blackout in Google AI Overviews and ChatGPT. This stark divide reveals that while LLMs recognize Mantis’s technical superiority in handling data fragmentation, the brand is failing to register in the broader search-generative ecosystem where legacy giants like Medidata and Veeva still dominate the narrative.

Strengths

  • Exceptional performance in Claude and Gemini for 'Modernizing Clinical Data Infrastructure' queries, reaching as high as position #2.
  • Strong resonance with Strategic Clinical Operations Leaders, achieving a 58% mention rate and high positive sentiment.
  • High technical authority in Claude specifically regarding 'data fragmentation in clinical trials,' where it consistently outperforms broader competitors.

Visibility Gaps

  • Total lack of visibility (0%) in Google AI Overviews across all tested queries, a critical failure in the search-generative experience.
  • Complete absence from the 'Modern alternatives to Veeva/Medidata' conversation, allowing legacy vendors to maintain their market capture.
  • Negligible presence in ChatGPT, where its average position of 22.0 effectively makes the brand undiscoverable for mainstream AI users.

Competitors in AI Recommendations

  • Snowflake: 20 mentions
  • Medidata Rave: 20 mentions
  • Medidata: 20 mentions
  • Veeva: 19 mentions
  • Databricks: 14 mentions
  • Veeva Vault: 13 mentions
  • Tableau: 12 mentions
  • dbt: 11 mentions
  • Saama Technologies: 10 mentions
  • Viedoc: 9 mentions
  • Veeva Vault CDMS: 9 mentions
  • Medrio: 9 mentions
  • OpenClinica: 9 mentions
  • Fivetran: 8 mentions
  • Informatica: 8 mentions

Categories: Healthcare Technology

Tags: YC25-26