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Why Ontic

A lot of companies are selling “AI governance.” Most of them are solving a different problem than we are. Some of them are solving a problem that doesn’t exist the way they think it does. Here’s an honest comparison.

What each approach actually does

ApproachWhat it solvesWhat it doesn’tWhat breaks
RAGGives the model better contextCheck whether the answer is supported by evidenceModel sounds confident. Answer is still wrong. Customer acts on it.
RLHFTrains the model to cooperateGuarantee it will — training is probabilistic, not deterministicModel cooperates — until it doesn’t. You find out from a user report.
GuardrailsFilters output after the model speaksPrevent someone from acting on the claim before the filter catches itFilter catches it after the response exists. Someone may have already seen it.
MonitoringTells you what happenedStop it from happeningDashboard shows the failure. After the damage.
OnticChecks claims against real data before they get outFix the model. (The model isn’t the problem.)Nothing — the claim never gets out.

Every other approach lets the claim exist first. We answer one question before it gets out: does the evidence exist? If not, the claim doesn’t get through.

We govern what you already run

No rip-and-replace. Ontic layers governance onto the stack you’ve already chosen — from frontier APIs to air-gapped appliances.

Base Model

Latest GPT/ClaudeSLMs / Quantized Models

Retrieval Stack

Provider BrowsingLanceDB, Qdrant, FAISS

Identity (IAM)

Google, MicrosoftCAC, YubiKey, Biometrics

Policy Engine

Provider ModerationOpen Policy Agent — OPA

Adversarial Defense

"Report Abuse" buttonNIST AI RMF Standards

Infrastructure

Shared GPU FleetNvidia IGX, Dell XR Servers

Cost Model

Per User / MonthHardware + Seat License

Compliance

Terms of ServiceAuthority to Operate.

When you don’t need Ontic

If your AI is writing internal drafts, brainstorming, or doing anything where a human always reviews before acting — you don’t need us. We’re built for when the output goes directly to someone who might act on it. If nobody acts on it, governance is overhead.