Verified claim · AI-ML · 100% confidence
Exa founded in: 2021 by Will Bryk + Jeff Wang — AI-native search API (formerly Metaphor) for LLM retrieval.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 805ca20c03f0797e
SourceScore rates how reliable a source is to cite — for AI answers and research. This is one verified claim from the catalog.
Structured fields
- Subject
- Exa
- Predicate
founded_in- Object
- 2021 by Will Bryk + Jeff Wang — AI-native search API (formerly Metaphor) for LLM retrieval
- Confidence
- 100%
- Tags
- exa · metaphor · ai-search · embedding-search · company-history · founded_in · 2021
Sources (2)
[1] docs · Y Combinator · 2024-03-20
Exa — Y Combinator company profile (formerly Metaphor)[2] docs · Exa · 2021-06-01
Exa — official site
Cite this claim
Ready-to-paste citation (Markdown / plain text):
Exa founded in: 2021 by Will Bryk + Jeff Wang — AI-native search API (formerly Metaphor) for LLM retrieval. — SourceScore Claim 805ca20c03f0797e (verified 2026-05-16). https://sourcescore.org/api/v1/claims/805ca20c03f0797e.jsonEmbed this claim
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Frequently asked questions
Is the claim "Exa founded in: 2021 by Will Bryk + Jeff Wang — AI-native search API (formerly Metaphor) for LLM retrieval." 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 "Exa founded in: 2021 by Will Bryk + Jeff Wang — AI-native search API (formerly Metaphor) for LLM retrieval."?
Evidence comes from 2 primary sources: Y Combinator, Exa. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/805ca20c03f0797e.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/805ca20c03f0797e.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/805ca20c03f0797e.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/805ca20c03f0797e.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "Exa founded in: 2021 by Will Bryk + Jeff Wang — AI-native search API (formerly Metaphor) for LLM retrieval."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/805ca20c03f0797e.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Exa founded in: 2021 by Will Bryk + Jeff Wang — AI-native search API (formerly Metaphor) for LLM retrieval."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_exa_fact() -> dict:
"""Fetch the verified SourceScore claim for Exa."""
r = httpx.get("https://sourcescore.org/api/v1/claims/805ca20c03f0797e.json")
return r.json()