SourceScore

Verified claim · AI-ML · 100% confidence

Vellum AI founded in: 2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23).

Last verified 2026-05-16 · Methodology veritas-v0.1 · bc80872c632bf77e

Structured fields

Subject
Vellum AI
Predicate
founded_in
Object
2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23)
Confidence
100%
Tags
vellum-ai · llm-platform · yc-w23 · company-history · founded_in · 2023

Sources (2)

  1. [1] docs · Vellum AI · 2023-01-30

    About Vellum AI
    Vellum AI is an LLM application development platform founded in 2023 by Akash Sharma, Sidd Seethepalli, and Noa Flaherty. The company is part of Y Combinator's W23 batch.
  2. [2] docs · Y Combinator · 2023-01-30

    Vellum AI on Y Combinator directory

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Ready-to-paste citation (Markdown / plain text):

Vellum AI founded in: 2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23). — SourceScore Claim bc80872c632bf77e (verified 2026-05-16). https://sourcescore.org/api/v1/claims/bc80872c632bf77e.json

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<iframe src="https://sourcescore.org/embed/claim/bc80872c632bf77e/" width="100%" height="360" frameborder="0" loading="lazy" title="Vellum AI founded in: 2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23)."></iframe>

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Frequently asked questions

Is the claim "Vellum AI founded in: 2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23)." verified?

Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.

What is the evidence for "Vellum AI founded in: 2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23)."?

Evidence comes from 2 primary sources: Vellum AI, Y Combinator. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/bc80872c632bf77e.json includes an HMAC-SHA256 signature for audit verification.

When was this claim last verified by SourceScore?

Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.

How can I cite this SourceScore claim in my code or article?

Fetch the signed JSON envelope from https://sourcescore.org/api/v1/claims/bc80872c632bf77e.json which includes the verbatim claim, primary sources, confidence, methodology version, last-verified date, and HMAC-SHA256 signature for audit. The CC-BY-4.0 license permits commercial use with attribution to SourceScore.

Use this claim in your code

Fetch this signed envelope from your application. The response includes the verbatim excerpt, primary source URLs, and an HMAC-SHA256 signature you can verify locally for audit trails.

cURL

curl https://sourcescore.org/api/v1/claims/bc80872c632bf77e.json

JavaScript / TypeScript

const r = await fetch("https://sourcescore.org/api/v1/claims/bc80872c632bf77e.json"); const envelope = await r.json(); console.log(envelope.claim.statement); // "Vellum AI founded in: 2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23)."

Python

import httpx r = httpx.get("https://sourcescore.org/api/v1/claims/bc80872c632bf77e.json") envelope = r.json() print(envelope["claim"]["statement"]) # "Vellum AI founded in: 2023 by Akash Sharma + Sidd Seethepalli + Noa Flaherty — LLM application development platform (YC W23)."

LangChain (retrieve-then-cite)

from langchain_core.tools import tool import httpx @tool def get_vellum_ai_fact() -> dict: """Fetch the verified SourceScore claim for Vellum AI.""" r = httpx.get("https://sourcescore.org/api/v1/claims/bc80872c632bf77e.json") return r.json()