{
  "apiVersion": "v1",
  "methodology": "https://sourcescore.org/methodology/",
  "canonical": "https://sourcescore.org/claims/2f9c856fbdd1a2c7/",
  "claim": {
    "vertical": "ai-ml",
    "subject": "Cohere Embed v4",
    "predicate": "publicly_released_on",
    "object": "2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages",
    "confidence": 1,
    "sources": [
      {
        "url": "https://cohere.com/blog/embed-4",
        "title": "Embed 4 — Multimodal Embeddings for Enterprise Search and RAG",
        "publisher": "Cohere",
        "publishedDate": "2025-04-09",
        "accessedDate": "2026-05-16",
        "type": "official-blog",
        "excerpt": "Embed 4, our latest multimodal embedding model designed to revolutionize how businesses search and retrieve information."
      },
      {
        "url": "https://docs.cohere.com/docs/embed",
        "title": "Cohere Embed documentation — embed-v4.0",
        "publisher": "Cohere",
        "publishedDate": "2025-04-09",
        "accessedDate": "2026-05-16",
        "type": "docs"
      }
    ],
    "publishedAt": "2026-05-16T00:00:00Z",
    "lastVerified": "2026-05-16",
    "methodologyVersion": "veritas-v0.1",
    "tags": [
      "embed-v4",
      "cohere",
      "embeddings",
      "multimodal",
      "rag",
      "released_on",
      "2025"
    ],
    "id": "2f9c856fbdd1a2c7",
    "statement": "Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages."
  },
  "signature": {
    "algorithm": "HMAC-SHA256",
    "signedBy": "did:web:sourcescore.org",
    "signedAt": "2026-05-29T00:00:00.000Z",
    "signature": "abdecb047e7601b4a8e3b758aea84974c4f213fba0d4f0d68789f0bf813e2620"
  },
  "citedAs": "Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages. — SourceScore Claim 2f9c856fbdd1a2c7 (verified 2026-05-16, signed abdecb04…). https://sourcescore.org/claims/2f9c856fbdd1a2c7/"
}