Verified claim · AI-ML · 100% confidence
Adept AI founded in: 2022 by David Luan + Niki Parmar + Ashish Vaswani — agent-AI company building action transformer models.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 8e33113147c2f543
Structured fields
- Subject
- Adept AI
- Predicate
founded_in- Object
- 2022 by David Luan + Niki Parmar + Ashish Vaswani — agent-AI company building action transformer models
- Confidence
- 100%
- Tags
- adept-ai · luan · parmar · vaswani · agent-company · act-1 · founded_in · 2022
Sources (2)
[1] official blog · Adept AI · 2022-09-14
ACT-1: Transformer for Actions“Adept, founded by AI veterans Niki Parmar, Ashish Vaswani, and David Luan, introduces ACT-1, our first transformer for actions.”
[2] official blog · Adept AI · 2022-04-01
Adept AI — official site
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Adept AI founded in: 2022 by David Luan + Niki Parmar + Ashish Vaswani — agent-AI company building action transformer models. — SourceScore Claim 8e33113147c2f543 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/8e33113147c2f543.jsonEmbed this claim
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Frequently asked questions
Is the claim "Adept AI founded in: 2022 by David Luan + Niki Parmar + Ashish Vaswani — agent-AI company building action transformer models." 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 "Adept AI founded in: 2022 by David Luan + Niki Parmar + Ashish Vaswani — agent-AI company building action transformer models."?
Evidence comes from 2 primary sources: Adept AI, Adept AI. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/8e33113147c2f543.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/8e33113147c2f543.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/8e33113147c2f543.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/8e33113147c2f543.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "Adept AI founded in: 2022 by David Luan + Niki Parmar + Ashish Vaswani — agent-AI company building action transformer models."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/8e33113147c2f543.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Adept AI founded in: 2022 by David Luan + Niki Parmar + Ashish Vaswani — agent-AI company building action transformer models."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_adept_ai_fact() -> dict:
"""Fetch the verified SourceScore claim for Adept AI."""
r = httpx.get("https://sourcescore.org/api/v1/claims/8e33113147c2f543.json")
return r.json()