AI Visibility Index / Industries / Search engines & vector databases

Most AI-visible search & vector databases (2026)

We scored 11 search & vector databases on how easily ChatGPT, Perplexity, Claude and AI agents can find, understand and use them. Typesense leads with 97/100. Data from our crawl on October 18, 2026; scores are a homepage snapshot, not live.

90

Search & vector databases average score

86

Whole-index average (+4 for this industry)

100%

of these sites miss “Question & answer content”

#ProductScoreCrawlersContentSchemaAgents
1Typesense
typesense.org
9710089100100
2Algolia
algolia.com
9610087100100
2Vespa
vespa.ai
969591100100
4LanceDB
lancedb.com
951009410083
4Meilisearch
meilisearch.com
951009410083
4Pinecone
pinecone.io
959587100100
7Weaviate
weaviate.io
93959410083
8Marqo
marqo.ai
92949410083
8Zilliz
zilliz.com
921008710083
10Qdrant
qdrant.tech
75100822062
11Chroma Technology Corp
chroma.com
6495712035

Sub-scores: Crawlers = AI crawler access, Content = answer-engine content, Schema = structured data, Agents = agent readiness (llms.txt, API/MCP). Ties share a rank.

Search & vector databases vs the whole index

AreaThis industryAll 538 sites
Overall score9086
AI crawler access9897
Answer-engine content8889
Structured data8571
Agent readiness8376

Most common gaps among search & vector databases

Question & answer content100% (index: 71%)
Fix: Add an FAQ answering the exact questions buyers ask ChatGPT ("best X for Y", "X vs Y", "how much does X cost").
Machine-usable interface (API / MCP)64% (index: 52%)
Fix: Expose an MCP server or OpenAPI spec and link it from llms.txt so agents can use your product, not just read about it.
Meta description45% (index: 21%)
Fix: Write a 50-160 char description stating exactly what the product does.
Open Graph tags18% (index: 8%)
Fix: Add og:title, og:description and og:image (1200x630).
JSON-LD structured data18% (index: 33%)
Fix: Add JSON-LD (generated below) so engines know your entity, product and pricing unambiguously.
Entity / product schema18% (index: 37%)
Fix: Add Organization + Product/SoftwareApplication schema with name, url, logo, sameAs (socials), offers.
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FAQ

Which search & vector databases are the most visible to AI search engines?

In our October 18, 2026 crawl, the top-scoring search & vector databases were Typesense (97/100), Algolia (96/100), Vespa (96/100). The score measures how easily ChatGPT, Perplexity, Claude and AI agents can crawl, understand and use each product's homepage.

How do search & vector databases compare with the rest of the AI Visibility Index?

The 11 search & vector databases we track average 90/100, 4 points above the 86/100 average across all 538 SaaS and AI sites in the index.

What is the most common AI visibility gap among search & vector databases?

100% of the search & vector databases we checked miss "Question & answer content" (vs 71% across the whole index). Fix: Add an FAQ answering the exact questions buyers ask ChatGPT ("best X for Y", "X vs Y", "how much does X cost").

How is the AI visibility score calculated?

RankRoot checks four areas on each homepage: AI crawler access (robots.txt rules for GPTBot, ClaudeBot, PerplexityBot and others), answer-engine content (title, headings, FAQ-style content, server-rendered text), structured data (JSON-LD, Organization/Product schema) and agent readiness (llms.txt, discoverable API or MCP server). Each area is scored 0 to 100 and combined into one score.

When was this data collected, and can a company update its score?

Scores are a snapshot from our crawler on October 18, 2026. They are not updated automatically. Anyone can rescan a site live for free, and we refresh the index periodically.

My search & vector database isn't listed. How do I see where it would rank?

Run a free scan at https://getrankroot.com/report. You get the same score and checks, so you can compare it directly with this leaderboard.

Other industry leaderboards

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Methodology and full findings: State of AI Visibility 2026. Industry labels are assigned by RankRoot from each product's own homepage description.