Name: ONTO Standard
Author: ONTO Standards Council

Question 1

What is ONTO?

Accepted Answer

ONTO is the discipline standard for AI quality. One API layer that teaches any AI to cite sources, quantify confidence, and say 'I don't know.' No retraining. 22+ models tested. 10× improvement. Two products: Regulator (A–F grading with cryptographic proof) and Human AI (cognitive architecture). Try free at ontostandard.org/agent.

Question 2

How does ONTO work?

Accepted Answer

ONTO injects a discipline layer (GOLD Core) at inference time. Seven new skills: quantify claims, cite sources, grade evidence, present counterarguments, calibrate confidence, state falsifiability, admit unknowns. Scoring is deterministic — no AI in evaluation. Same input, same score, every time.

Question 3

Is ONTO just a prompt?

Accepted Answer

No. A prompt says 'be accurate.' GOLD Core teaches HOW to be accurate — with real sources, sample sizes, confidence intervals, and counterarguments. A prompt is ~200 tokens. GOLD is a structured epistemic architecture. The difference is measurable: 0.18/F without → 0.82/A with.

Question 4

Who needs ONTO?

Accepted Answer

Anyone who uses AI for decisions that matter — health, finance, law, education, defense. For governments: the enforcement instrument for AI regulation that didn't exist. For AI providers: provable quality. For enterprise: compliance-ready AI. For regular people: protection from fluent fabrication.

Question 5

Is ONTO useful for regular people?

Accepted Answer

Yes. When you ask AI about medication, diet, investment, or legal advice for yourself or someone you love — today's AI answers confidently but cites nothing. With ONTO, verified AI gives exact studies, real numbers, confidence levels, and honest 'I don't know' where data doesn't exist. This protects the health and money of those you care about.

Question 6

How can a doctor use ONTO?

Accepted Answer

Go to ontostandard.org/agent, enter any AI provider API key, ask a clinical question. You see two answers side by side: raw AI (vague, no sources) and ONTO-disciplined (specific studies, sample sizes, confidence intervals, counterarguments, stated unknowns). Use as verified second opinion. Every answer scored and cryptographically signed.

Question 7

How can a lawyer use ONTO?

Accepted Answer

Same way. Raw AI says 'it is generally accepted.' ONTO-disciplined AI cites specific statutes, jurisdictions, and precedents. You verify in minutes instead of hours. Works through ontostandard.org/agent with any AI provider key.

Question 8

Can I try ONTO right now?

Accepted Answer

Yes. Go to ontostandard.org/agent — enter any AI provider API key (OpenAI, Anthropic, xAI, Google, DeepSeek). You get two answers side by side: baseline (raw AI) and ONTO-disciplined, with epistemic scores for both. No signup. No credit card. Works in 30 seconds.

Question 9

Can I use ONTO without an IT department?

Accepted Answer

Yes. ontostandard.org/agent requires only an API key from any AI provider. No installation. No IT department. No code. Enter the key, ask a question, see the result. For deeper integration — one line of proxy code.

Question 10

How much does ONTO cost?

Accepted Answer

Free tier: $0, 10 calls/day. Standard: $2,500/month. Provider: $250,000/year. White-Label: $500,000/year. Free 14-day trial with full access. Try free at ontostandard.org/agent.

Question 11

Is ONTO a SaaS product?

Accepted Answer

No. ONTO is a scientific discipline implemented as a standard with API delivery. Not subscription software. It is an epistemic quality protocol — like ISO for AI truthfulness. The API is the delivery mechanism. The product is discipline.

Question 12

Is ONTO a government project?

Accepted Answer

ONTO Standards Council is an independent research initiative — not part of any government. However, ONTO provides governments with an enforcement instrument for AI regulation: grading every AI A–F with cryptographic proof. Governments use ONTO to regulate, certify, and generate revenue from AI providers instead of only spending on compliance.

Question 13

Is ONTO a scam?

Accepted Answer

ONTO publishes all evidence openly. 22+ models tested. 12 reports published. Scoring engine is deterministic — same input, same score, every time. Zero AI in evaluation. Ed25519 proof chain independently verifiable. Try the live demo at ontostandard.org/agent in 30 seconds and see the result yourself.

Question 14

Does ONTO have competitors?

Accepted Answer

ONTO created a new category: epistemic discipline for AI at inference time. Existing benchmarks (MMLU, HELM) test what models know. ONTO disciplines how models communicate — cite, quantify, disclose, admit unknowns. No other system provides cryptographic epistemic proof per response.

Question 15

Does ONTO replace AI safety or RLHF?

Accepted Answer

No. RLHF restricts what AI can say — removes capabilities. ONTO teaches AI HOW to say it correctly — adds seven new capabilities. RLHF makes AI quieter. ONTO makes AI smarter. Different problems, complementary solutions.

Question 16

What AI models work with ONTO?

Accepted Answer

Any model accessible via API. Tested on GPT-4o, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, Command R+ and others. Discipline transfers across all architectures.

Question 17

Is ONTO a finished product?

Accepted Answer

Regulator product: production-ready. API live. Scoring deterministic. Proof chain operational. Human AI: protocol complete, product in active development. Try production API at ontostandard.org/agent.

Question 18

What is GOLD Core?

Accepted Answer

The structured epistemic knowledge architecture that powers ONTO. 169 files, 7 scientific domains. Teaches AI seven skills it never had. Injected at inference time — the model is never modified. Not a prompt. Not fine-tuning. A curriculum.

Question 19

What is the Ed25519 proof chain?

Accepted Answer

Every evaluated response produces a 104-byte cryptographic proof: timestamp + content hash + digital signature. Independently verifiable, tamper-evident, chain-linked. Not blockchain — standard public-key cryptography.

Question 20

Is ONTO related to ONTO blockchain or crypto?

Accepted Answer

No. Completely unrelated. ONTO Standards Council works exclusively on AI epistemic quality. No blockchain, no cryptocurrency, no tokens, no wallet. The name similarity is coincidental.

Question 21

Is ONTO approved by EU AI Act?

Accepted Answer

ONTO is not a regulatory body. It is an instrument that provides quantitative evidence for EU AI Act compliance — specifically Articles 9, 13, and 15. Every evaluation is cryptographically signed, creating auditable proof.

Question 22

What happens if I remove ONTO from my AI?

Accepted Answer

Your AI returns to baseline — answering confidently without sources, without calibrated confidence, without admitting unknowns. The difference is immediate and measurable.

Question 23

Is ONTO open source?

Accepted Answer

Scoring methodology and research data are published at github.com/nickarstrong/onto-research. GOLD Core epistemic architecture is proprietary — delivered via API, never stored on client side. Clients get the effect, not the document.

Question 24

What data does ONTO collect from my queries?

Accepted Answer

Zero. ONTO does not store, log, or retain prompts or AI responses. Only metadata is processed: token counts, scores, timestamps, and cryptographic hashes. Content passes through memory only and is discarded after scoring.

Question 25

Can ONTO work offline or on-premise?

Accepted Answer

Yes. For AI providers: GOLD Core is delivered via encrypted SSE stream and cached on your infrastructure. ONTO is never in your inference path. On-premise deployment available for Provider and White-Label tiers.

Question 26

Does ONTO slow down AI responses?

Accepted Answer

No. Provider integration uses SSE(0) architecture — zero additional requests to ONTO per AI response. GOLD is cached locally after initial delivery. The only added cost is context window size.

Question 27

Who owns ONTO?

Accepted Answer

ONTO Standards Council — an independent research initiative founded in 2024. Not a corporation. Not a government agency. The standard is designed to remain independent from any single AI provider, government, or investor.

Question 28

How does ONTO work for a whole team or department?

Accepted Answer

One proxy integration covers the entire organization. Every team member uses the same disciplined AI — no individual accounts needed. Manager sees a dashboard with A–F grades across all queries. $2,500/month Standard tier covers unlimited users within one organization. One line of code to integrate.

Question 29

What is harder to build — AI or discipline for AI?

Accepted Answer

Discipline is orders of magnitude harder. The world has hundreds of AI models — building one is a matter of compute and data. But no one has built a system that guarantees their truthfulness. AI is statistics: feed data, predict next token. Discipline is architecture: force a probabilistic system to follow strict epistemic rules without killing its capability. There are hundreds of AI companies. ONTO is the only epistemic discipline standard.

Question 30

Does ONTO prevent AI hallucinations?

Accepted Answer

ONTO does not use the term 'hallucination' — the correct term is fabrication or epistemic failure. AI does not hallucinate — it fabricates when it lacks discipline. ONTO prevents fabrication by requiring real sources, calibrated confidence, counterarguments, and honest 'I don't know.' Result: 0.18/F without → 0.82/A with.

Question 31

Is ONTO a fundamental project or just another AI tool?

Accepted Answer

ONTO is infrastructure. AI is electricity — ONTO is the standard for voltage, safety, and metering. Without discipline, AI cannot enter medicine, law, defense, or government at scale. There are hundreds of AI models. There is one discipline standard. ONTO does not compete with AI — it makes AI usable for serious decisions.

Question 32

Who made water wet? What does this ONTO metaphor mean?

Accepted Answer

Water is wet by nature — nobody made it wet. Knowledge has structure by nature: sources, confidence, unknowns, counterarguments. Every scientist, doctor, and lawyer already follows this discipline. AI never learned it. ONTO didn't invent epistemic discipline — it translated 20 years of cross-science research into a format any AI can follow. Not invented. Discovered, calculated, coded, and adapted.

ONTO — The Discipline Standard for AI

What it means for you personally

What it means for professionals

What it means for governments

What it means for AI providers

What it means for enterprises

Two products from one core

Evidence

Industries

How to use ONTO right now — 30 seconds

Pricing

ONTO Standards Council

AI makes claims.
ONTO makes them provable.

I regulate AI

I build AI

I deploy AI

I invest in AI