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Veritize verifies every AI output against your sources before your product shows it to a user. Cite-checking, fact-grounding, drift detection, and policy checks all run before publish, not after support is already cleaning up the damage.
Point Veritize at the places your team already drafts. It watches new documents, email threads, PRs, and slides appear, then checks each one against the sources, baselines, and policy rules you actually trust.
Every unverified claim is a discovery risk. Veritize checks every artifact against the policies you actually have to defend, marketing claims, medical copy, financial statements, regulatory filings, legal advice, and flags the specific sentence, with the specific rule it violated.
# Spec for an investor-facing memo spec: claims-memo-v2 mode: inline-block structural: schema: memo.schema.json max_length: 1200 factual: every_numeric_claim: requires-source citation_provider: DeepTap internal_kpi_source: ledger://finance.kpi safety: pii: block absolute_claims: block forbidden_phrases: ./lists/legal-4.2.1 format: markdown_only: true no_trailing_html: true semantic: tone: factual reading_grade: <= 12
artifact_id: drf_9f2a score: 0.61 verdict: block latency_ms: 480 findings: - evaluator: factual.numeric_claim claim: "340% YoY growth" source_found: false action: block - evaluator: factual.quote_attribution target: "Gartner" corroboration: 0.14 action: warn - evaluator: safety.absolute_claim span: "the leader in..." action: block retry_hint: "Cite internal KPI ledger"
JSON Schema, Zod, Pydantic, or OpenAPI, object must parse and validate before anything else runs.
Declared shape: required keys, required claim types, required sections.
Every cited number matched back to a ledger, DeepTap fact, or cited URL.
Quoted statements must be traceable to the attributed speaker or publication.
Emails, phone numbers, SSNs, health identifiers, account numbers, regex + NER.
Forbidden phrases, absolute claims, regulated terminology, per-jurisdiction lists.
Trailing HTML, mismatched code fences, stray tokens, model artifact detection.
Word/char ranges, reading grade, tone constraints, fast heuristics before LLMs.
Compares output against prior outputs and your knowledge base for contradictions.
Does this answer actually address the prompt? Embeds + LLM judge as fallback.
Write a ContextWorker. Plug it into the pipeline. Get the same observability.
AND/OR/NOT trees over any evaluator. Escalate on severity, not on count.
Add one line to your agent's harness. Every PLAN, EXECUTE, and VERIFY step runs through Veritize before it writes a file, merges a PR, or sends a message. STOKE-traced. Artifact-addressed. Replayable.
Knowledge engine. Resolves every factual evaluator call with cited, decaying, confidence-scored facts.
Routes every AI request through Veritize when policy requires verification, including retroactive reroute.
ContextWorkers invoke verify() inline, mutate on warn, block on fail. Zero extra hop.
Every agent turn traced, verified, and replayable. Verify step lives between EXECUTE and COMMIT.
Agent-first hosting. verify() is a first-class primitive in the Heroa SDK, no gateway required.
Every scheduled assistant run lands in Tasks with its verify report attached. Human sees the flags first.
Point-and-click skill marketplace. Every skill ships with a default verify spec; swap yours in.
Persistent coding environments. Verify hooks into the pre-commit loop for hallucinated APIs and phantom imports.
Wire Veritize into one channel today. See the first flags in an hour. Decide what blocks, what retries, and what your team just needs to know about.