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4D Molecular Therapeutics

4dmoleculartherapeutics.com · Technology · FDMT

Ranked 431 of 2,047 companies in the study

40Overall score
  • Visibility7
  • Citations0
  • Sentiment100
  • Site quality87
  • AI readiness36
What this means for 4D Molecular Therapeutics

AI assistants rarely name 4D Molecular Therapeutics. They mention the company in 1 of 60 answers. Its overall score is 40 out of 100, ranking 431st of 2,047 companies and 69th of 273 in the Technology sector. The website passes 5 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about the technology market: none named 4D Molecular Therapeutics. AI assistants named it in 1 of 60 answers (1.7%). The typical technology company is named in 10.0% of answers. By how often it is named, 4D Molecular Therapeutics ranks 211 of 273 in its sector.

Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its rivals.

Named by AI in
1.7%
1 of 60 answers
Share of mentions
14.3%
compared with 5 rivals
AI readiness
5/14
technical checks passed. Typical for its sector: 4
Rank in its sector
69 of 273
by overall score, where the typical technology company scores 36
How 4D Molecular Therapeutics compares with all 2,047 companies

Every dot is a company in the study. Hover one to see it; click to open its report.

This companySame sectorEvery other companyNever named

What makes up the score

Five parts, each scored out of 100.

Visibility
7

How often AI assistants name the company

Citations
0

How often AI uses the company's own website as a source

Sentiment
100

How positively AI describes the company

Site quality
87

How well built the website's own pages are

AI readiness
36

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Compared with technology

273 companies in this sector. The line on each bar is the typical company.

Overall score40
Ranks 69 of 273. Typical company: 36
Named in answers2%
Ranks 211 of 273. Typical company: 10%
AI readiness36
Ranks 36 of 273. Typical company: 29
What Claude actually said

An answer that names the company

“Which innovative genetic medicine platforms show promise for large market diseases?”

Based on recent developments in the field, several innovative genetic medicine platforms show significant promise for large market diseases:

Key Technology Platforms

The major technology platforms include adeno-associated viral (AAV) vectors for in vivo gene delivery, CRISPR/Cas9 gene editing for precise genetic correction, and emerging in vivo gene writing approaches that promise programmable genome modification without ex vivo cell processing.

AAV-Based Platforms

Viral vector platforms dominate the market segment with the largest revenue share of 58.1% in 2024. 4D Molecular Therape …

The AI’s answer as we received it, shortened and not checked for accuracy.

Share of mentions

How the mentions in these answers were split between this company and its rivals

4D Molecular Therapeutics
50.0%
Sarepta Therapeutics
50.0%
uniQure
0.0%
Regenxbio
0.0%
Voyager Therapeutics
0.0%
Krystal Biotech
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

Claude
1/15
Gemini
0/15
Perplexity
0/15
OpenAI
0/15
Ready for AI agents

What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals
Show every check, for your technical team
Discoverability
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 92.0%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 86.8%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 0.3%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 5.5%
Content accessibility
50 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 1.9%
  • llms.txtPassed

    An llms.txt that tells language models what the site offers.

    study: 25.1%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 93.4%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 1.4%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.2%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 0.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 11.8%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 10.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.0%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.2%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.1%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 0.2%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 33.7%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.1%

Score 36 of 100 · 97% of checks could run · checked on October 5, 2026 · 4dmoleculartherapeutics.com · 2,047 companies scanned

See how every company did, and how this was measured.

The checks behind the AI readiness score

5 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.

These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.

Show the 14 checks
Discoverability
  • Passedrobots.txt publishedstudy: 85.0%
  • PassedXML sitemapstudy: 73.2%
  • PassedHTTP Link headers (RFC 8288)study: 29.0%
Content Accessibility
  • Not metMarkdown content negotiationstudy: 8.3%
  • Passedllms.txt publishedstudy: 21.7%
  • PassedToken budget (page weight)study: 95.2%
Bot Access Control
  • Not metExplicit AI bot rulesstudy: 13.0%
API / Auth / MCP
  • Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
  • Not metOAuth Authorization Server discoverystudy: 10.1%
  • Not metOAuth Protected Resource discoverystudy: 9.3%
  • Not metMCP Server Cardstudy: 0.0%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 4.2%
  • Not metAgent Skills declaredstudy: 0.0%
What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 84% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI
  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly
AI search
  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly
Answering questions
  • ChatGPT-Userpartly
  • Claude-Userpartly
  • Perplexity-Userpartly
  • DuckAssistBotpartly
  • MistralAI-Userpartly

Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.

Websites the AI used as sources

How many times each website was listed as a source in these answers

pmc.ncbi.nlm.nih.gov
132
nature.com
35
onlinelibrary.wiley.com
22
ncbi.nlm.nih.gov
17
fda.gov
17
frontiersin.org
17
pubmed.ncbi.nlm.nih.gov
15
sciencedirect.com
12
link.springer.com
11
synapse.patsnap.com
9

In the study as US-listed.

Every question, and where the company came up (1 of 15)
QuestionOpenAIClaudePerplexityGemini
  • Which emerging non-genetic treatment options compare to gene medicines for rare diseases?
  • Are there programs that help patients access advanced gene therapies at lower out-of-pocket costs?
  • What should healthcare providers look for when evaluating next-generation genetic medicine solutions?
  • Are advanced gene therapies with customized vectors worth considering for patients with unmet medical needs?
  • What advancements are shaping the future landscape of curative intent genetic therapies?
  • Which patient populations benefit most from precision-targeted gene therapies?
  • What are the main alternatives to gene therapy for inherited metabolic disorders?
  • What are common challenges in delivering genetic medicines to hard-to-reach tissues?
  • How does an engineered viral vector platform differ from naturally occurring viral vectors in gene therapy?
  • What factors influence the cost of genetic medicines for serious inherited diseases in the US?
  • AAV-based gene delivery vs. lentiviral vectors: which is better for central nervous system disorders?
  • Which innovative genetic medicine platforms show promise for large market diseases?
  • What are the best gene therapy options for treating rare genetic diseases in adults?
  • How are engineered vectors being used to target previously untreatable genetic disorders?
  • Why might a gene therapy not provide lasting effects in a patient with a hereditary condition?
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.

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