AI Watermark¶

Every AI-generated response is stamped with a latent HMAC-SHA256 watermark recorded in a log, so later you can answer "did this deployment write this text?" — and detect whether it was edited since. One endpoint does the checking, in three modes depending on what you still have: the text, the identifiers, or both.

Endpoints¶

POST /v1/glad/watermark/verify¶

What it does. Answers "did this deployment generate this text?" One endpoint, three modes, chosen automatically by what you send:

Sending none of those returns 400.

# live — full integrity check
curl -s -X POST http://localhost:8080/v1/glad/watermark/verify \
  -H "Content-Type: application/json" \
  -d '{
    "call_id":       "call_abc123",
    "watermark_id":  "a8b3c1d4e5f6…",
    "response_text": "The capital of France is Paris."
  }' | jq

# search — just paste the text
curl -s -X POST http://localhost:8080/v1/glad/watermark/verify \
  -H "Content-Type: application/json" \
  -d '{"text": "The capital of France is Paris."}' | jq '{valid, call_id, match_mode}'

import httpx

def verify(text: str, call_id: str | None = None, watermark_id: str | None = None):
    body = {"response_text": text}
    if call_id and watermark_id:
        body |= {"call_id": call_id, "watermark_id": watermark_id}
    r = httpx.post("http://localhost:8080/v1/glad/watermark/verify", json=body, timeout=60)
    r.raise_for_status()                      # 400 when the body identifies nothing
    return r.json()

res = verify("The capital of France is Paris.", "call_abc123", "a8b3c1d4e5f6…")
print(res["mode"], res["valid"])
print(res["message"])

async function verify(text: string, callId?: string, watermarkId?: string) {
  const body: Record<string, string> = { response_text: text }
  if (callId && watermarkId) { body.call_id = callId; body.watermark_id = watermarkId }
  const r = await fetch("http://localhost:8080/v1/glad/watermark/verify", {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify(body),
  })
  if (!r.ok) throw new Error(await r.text())
  return r.json()
}

const res = await verify("The capital of France is Paris.", "call_abc123", "a8b3c1d4e5f6…")
console.log(res.mode, res.valid, res.message)

What comes back¶

{
  "verification_id": "VRF-3F9A1C7B2E5D8046A1B2",
  "valid": true,
  "call_id": "call_abc123",
  "watermark_id": "a8b3c1d4e5f6…",
  "method": "hmac_sha256_v1",
  "mode": "live",
  "timestamp": "2026-06-10T10:23:45Z",
  "verified_at": "2026-06-18T09:00:00+00:00",
  "applicable_laws": ["EU_AI_ACT", "CA_SB_942"],
  "lang": "en",
  "message": "Verification successful. The watermark_id matches the response text. …",
  "provider": "Geodesia S.R.L.",
  "product_version": "…"
}

Request fields¶

What Is an AI Watermark?¶

An AI watermark is a signal embedded in the text output of a language model that allows the origin of the text to be verified. Unlike visible watermarks, Geodesia's watermark is latent — it is not visible in the text but is recoverable through the verification endpoint.

This satisfies:

• EU AI Act Article 50 — AI-generated content must be marked in a way that is detectable
• California SB 942 — AI-generated content must carry detectable disclosure
• Italy 132/2025 — AI content marking requirements

The watermark is a cryptographic HMAC computed over the generation parameters and embedded as metadata attached to the response. The manifest watermark (explicit disclosure in the geodesia.watermark response field) is delivered alongside the latent one.

How It Works¶

When Geodesia generates a response, it:

1. Computes HMAC-SHA256(watermark_key, session_id + call_id + timestamp + model_id)
2. Attaches the result as the watermark_token in the response metadata
3. Records the watermark in the audit chain

To verify, you provide the watermark_token and the relevant metadata. The verifier recomputes the HMAC and checks if the provided token matches.

The watermark_key is derived from your deployment's license token. It never leaves the server.

Response Disclosure¶

Every Geodesia G-1 response includes a manifest watermark in the geodesia.watermark field:

{
  "geodesia": {
    "watermark": {
      "token": "hmac:v1:a8b3c1d4e5f6...",
      "generated_by": "Geodesia G-1",
      "call_id": "call_abc123",
      "timestamp": "2026-06-10T10:23:45Z",
      "disclosure": "This content was generated by an AI system."
    }
  }
}

Watermark Configuration¶

Configure watermarking in config.yaml:

watermark:
  enabled: true
  algorithm: "hmac_sha256"
  include_in_response: true       # Include watermark in all API responses
  disclosure_text: "This content was generated by an AI system."
  custom_disclosure: null         # Override with jurisdiction-specific text

Regulatory Coverage¶