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Agent Readiness Index

Velaura AI Agent Readiness Score

Partially Agent-Ready · Grade D · Scanned August 19, 2026

Velaura AI develops ultra-low power silicon and software technologies for AI infrastructure, focusing on energy efficiency for data centers and physical AI applications.

Semiconductors
Artificial Intelligence
$110M raised
61 employees
Santa Clara, United States
47
/ 100
Grade D
Six-dimension breakdown

Discoverability

Can an AI agent find sitemaps, llms.txt, and machine-readable entry points?

100

Content

Can agents consume content cheaply via markdown, schema.org, and structured data?

43

Access Control

Are crawl rules and AI bot permissions declared in robots.txt?

70

Capabilities

Does the site expose APIs, MCP endpoints, or agent-usable tools?

27

Commerce

Can agents discover pricing and initiate payments (x402, MPP, UCP)?

33

Quality

Performance, token efficiency, and trust signals beyond baseline checks.

55
Priority fixes

Capabilities (27/100)

Improve capabilities signals: llms.txt, robots.txt AI rules, structured data, MCP or OpenAPI endpoints, and agent-readable pricing where relevant.

Commerce (33/100)

Improve commerce signals: llms.txt, robots.txt AI rules, structured data, MCP or OpenAPI endpoints, and agent-readable pricing where relevant.

Content (43/100)

Improve content signals: llms.txt, robots.txt AI rules, structured data, MCP or OpenAPI endpoints, and agent-readable pricing where relevant.

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How we score

StartupHub audits the full website across 50+ checks: discoverability, content negotiation, access control, capabilities (API/MCP), commerce (x402/MPP), and quality.

Unlike pricing-only indexes, we measure whether AI agents can find, read, and act on the entire site, not just the pricing page.

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