Prediction Integrity
Pre-outcome proof for AI predictions and event markets. Cryptographically signed verification receipts and tamper-evident audit trails — for forecasts, market snapshots, and resolution records.
CertifiedData proves the record. DecisionLedger proves the process. Together, they form the trust layer for AI forecasting platforms, event markets, and autonomous decision systems.
The trust problem in AI predictions
Prediction platforms publish forecasts that influence financial, operational, and reputational decisions — but the record itself is rarely tamper-evident.
Records can be silently changed
A prediction published before an outcome can be edited, deleted, or backfilled after the result is known. Without a tamper-evident record, no party can prove what the system actually claimed in advance.
Selective disclosure is hard to detect
Operators can publish only the predictions that turned out well. Without a daily manifest of the full prediction set, an outsider cannot verify that the published archive is complete.
Resolution evidence is opaque
Event-market resolution depends on a resolver action that records the outcome. If the resolution payload and evidence reference are not signed and timestamped, the record can be revised silently.
AI forecast lineage is missing
Most forecast platforms cannot show which model version produced a prediction, what data it referenced, or whether the forecast was reviewed before publication. The output is delivered without provenance.
Pre-outcome proof
The only meaningful time to certify a prediction is before the outcome is known. Once the result has been observed, a record produced after the fact cannot prove what the system claimed in advance. Pre-outcome proof is the structural commitment that makes prediction integrity meaningful to a third party — without it, every archive is a marketing surface.
CertifiedData certifies predictions at issuance time. The certificate binds the prediction payload to a SHA-256 fingerprint, signs it with an Ed25519 private key, and records an ISO-8601 timestamp inside the signed payload. The signature covers the canonicalized bytes (RFC 8785 JSON Canonicalization Scheme), so the timestamp, payload, and signing key identifier are all bound together as a single tamper-evident artifact.
Any modification to the prediction after certification breaks the signature. Any attempt to backdate a prediction would require a new certificate with an earlier timestamp — but the signing log, the chain hash, and the certificate transparency log all make such backdating detectable. The proof model holds without trusting the platform that issued the prediction.
Why this is different from a regular prediction archive
Four structural properties that separate a CertifiedData prediction archive from a CMS-driven one. Each is independently necessary.
Pre-outcome timestamping by design
The certificate is issued at the moment the prediction is generated — not at archive time, not after settlement, not as a periodic batch job. The predicted_at timestamp lives inside the signed payload, so the proof binds the prediction to a moment that cannot be revised retroactively.
Tamper-evident, not just append-only
Append-only systems can be replayed or rebuilt. Tamper-evident records are cryptographically self-checking: the Ed25519 signature over the canonicalized payload makes any modification detectable using only the public signing key. No reliance on the platform's internal log integrity.
Independent verification with no platform access
Verifiers do not need a CertifiedData account, an API key, or any agreement with the issuing platform. The public key is published at /.well-known/signing-keys.json. The verification algorithm is deterministic. Any party can validate the receipt offline.
Schema-light, content-heavy
The prediction payload schema lives in the signed content itself — artifact_type and artifact_schema are payload fields, not database columns. Platforms can evolve the schema by issuing certificates with new artifact_schema values; the verification logic stays unchanged.
Who builds on prediction integrity
Audiences who consume prediction integrity infrastructure — either as platform operators integrating the API or as downstream parties verifying records.
| Role | What they need |
|---|---|
| Compliance and audit teams | Provable evidence that AI forecasts were issued in advance, were not revised post-outcome, and that the full prediction set is disclosed. Verifiable by external auditors without platform access. |
| Platform product leaders | Trust differentiation versus competitors. A signed-receipt archive is a structural feature that cannot be copied without similar infrastructure investment. |
| Data vendors and publishers | Customer-facing verification for the data products sold — market snapshots, forecast archives, AI research outputs. Verifiable cites for academic and institutional users. |
| Researchers and benchmark authors | Citable, replicable evidence for AI forecasting studies — including model lineage, training data references, and pre-outcome timestamps that survive paper review cycles. |
CertifiedData + DecisionLedger architecture
Two complementary layers. One proves the artifact. The other explains the lifecycle.
- →Hashes the prediction payload with SHA-256
- →Signs the payload with Ed25519
- →Issues a structured certificate with timestamp
- →Stores the entry in the public transparency log
- →Records the model version that produced the forecast
- →Logs input data references and approval events
- →Captures resolution actions and resolver identity
- →Links every event into an append-only chain
Explore prediction integrity
Machine-readable summary
{
"concept": "Prediction Integrity",
"concept_type": "category-hub",
"canonical_url": "https://certifieddata.io/prediction-integrity",
"parent_concept": null,
"related_concepts": [
"Certified predictions",
"Daily prediction manifest",
"AI artifact verification",
"Decision Ledger",
"AI artifact certification"
],
"schema_versions": [
"prediction_receipt.v1",
"prediction_manifest.v1"
],
"signing_algorithm": "Ed25519",
"hash_algorithm": "SHA-256 (RFC 8785 canonicalized)",
"verification_surface": "GET /api/verify/:certId",
"signing_keys_discovery": "/.well-known/signing-keys.json",
"positioning": "CertifiedData proves the prediction record. DecisionLedger proves the prediction process."
}Machine pointers
- canonical_url
- https://certifieddata.io/prediction-integrity
- concept_type
- category-hub
- primary_keyword
- prediction integrity
- related_concepts
- certified predictions · daily prediction manifest · ai forecast audit trail · ai artifact verification
- issuance_endpoint
- POST /api/notary/create (with prediction payload convention)
- verification_endpoint
- GET /api/verify/:certId
- public_key_url
- https://certifieddata.io/.well-known/signing-keys.json
- artifact_schemas
- prediction_receipt.v1, prediction_manifest.v1
Start certifying predictions
Hash the prediction payload. Sign it with Ed25519. Get a structured, machine-verifiable receipt that any party can validate without trusting the issuer.