What is release control infrastructure for AI?

Release control infrastructure is the software layer that inspects AI-generated business work products (reports, financial models, recommendations) at the release boundary before downstream delivery. It enforces deterministic evidence binding, calculations replay, and policy rules to assign explicit Release, Hold, or Block verdicts.

What is the difference between model evaluation and AI verification?

Model evaluation assesses aggregate model capability across benchmark test suites to determine if a model belongs in a tech stack. AI verification inspects a single specific AI output against current source-of-record evidence and business policy to determine if that specific artifact can be defended and released.

What is an AI release boundary?

The release boundary is the final operational control checkpoint between AI generation and downstream business execution. It is where AI output, source evidence, deterministic checks, and human judgment converge to yield an audit-proof release decision.

What are Veracity's 3-state release verdicts?

Veracity evaluates work against business policy to issue one of three explicit verdicts: Release (all configured evidence and rule checks pass), Hold (unresolved claims or missing evidence requiring targeted human review), or Block (material policy failure or data contradiction preventing downstream delivery).

AI verification at the release boundary

VERACITY

Veracity checks supported AI-generated work against source-of-record evidence and the business rules that govern a consequential workflow before it moves downstream.

What it is AI verification before release.

Who it is for Teams accountable for high-stakes AI-generated decisions.

What changes The AI-generated output gets a visible decision before downstream use.

What you get Release / Hold / Block with the evidence behind each claim.

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Who Vera is

Vera is the verification interface inside Veracity.

Veracity uses Vera to surface what the AI-generated artifact says, what evidence supports it and what the configured checks allow before release. Vera is not the LLM that generated the artifact; Vera is the deterministic verifier experience applied to the artifact under review.

Starts with the AI-generated artifact Vera begins with the artifact and the claims it makes.
Surfaces evidence and checks Vera connects supported claims to source evidence and configured checks.
Makes the decision legible Vera makes Release / Hold / Block clear before the artifact moves downstream.

Checking Decision pending

Vera is evaluating the AI-generated artifact against its evidence and configured checks.

The decision changes with the evidence available to the workflow.

Representative workflow examples (tailored to your environment)

Insurance

Loss ratio & policy exclusion clause verification.

Re-compute AI loss ratio calculations and verify binding policy exclusion clauses against primary loss runs before underwriting binder release.

Financial services

Debt covenant & financial model math tie-outs.

Re-compute financial model formulas, leverage ratios, and debt covenant terms in AI investment committee memos before capital deployment.

Legal

Contract review & regulatory filing provenance audit.

Map AI-extracted regulatory disclosures, SEC filings, and cross-indemnification clauses to authoritative statutory source text prior to executive sign-off.

Accounting

Tax provisions, revenue schedules & audit workpaper math.

Deterministically recalculate tax provision formulas, ASC 606 revenue schedules, and ledger balances before AI work enters the permanent audit record.

Don't see your industry or workflow? We custom-tailor release boundaries for your exact use case.

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What Vera sees

The AI-generated output alongside its evidence and configured checks.

A plausible output is not release-ready until its claims satisfy the workflow's business rules and source evidence. Rules are configurable by regulatory and compliance requirements, companies, and other stakeholders.

Source-of-record evidence Business rules Release decision

AI-generated artifact Q3 margin outlook 14%

Source records

Business rules

Release Block

Adjacent categories and Veracity's role
Category	Primary question	Veracity's Role
Model evaluation	How a system behaves across benchmarks or test sets	Complements model evaluation by checking the specific AI-generated work product and its evidence.
Observability	What a model, agent or system did over time	Draws on observability's trace context, but focuses on whether the supported AI-generated work can proceed.
GRC and policy systems	What policies, controls and approvals govern the organization	Applies workflow-specific requirements at the AI-generated work and release boundary.
Cybersecurity tooling	Whether systems, assets or data are exposed to security threats	Addresses a different control surface: whether an AI-generated artifact has the evidentiary support required to move downstream.
Human review	Who resolves exceptions and approves the next action	Keeps people accountable by making the evidence and any open questions explicit.
Veracity	Whether supported AI-generated work satisfies the workflow's business rules and evidence requirements to proceed	Returns Release / Hold / Block and keeps the verification record attached.

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Follow the release boundary from AI-generated artifact to evidence-backed decision.

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