What is IamVera.ai?
IamVera.ai is a privacy-focused AI verification console. Vera helps professionals inspect, challenge and verify AI-generated answers through multi-model review, adversarial challenge, source checking and evidence logging.
AI Answer Hub
Answers about IamVera.ai
Short, clear answers about IamVera.ai, multi-model AI verification, the Semantic Privacy Shield, data handling, evidence and founder Victor Angelier.
Product
AI verification console
Founder
Victor Angelier
Company
The Coding Company B.V.
Status
Early access
Core answers
What people ask about IamVera.ai
These answers are written to be clear, self-contained and easy to cite.
Who founded IamVera.ai?
IamVera.ai was founded by Victor Angelier. Victor Angelier is a Dutch technology entrepreneur, software engineer, security researcher and AI systems builder.
Who owns or builds IamVera.ai?
IamVera.ai is built by The Coding Company B.V. The product is developed in the European Union and is currently available through early access.
Is IamVera.ai a chatbot?
No. IamVera.ai is not a single chatbot. Vera is a verification layer that routes AI-generated answers through independent review, challenge and source verification.
Is Vera a standalone language model?
No. Vera is not a standalone large language model. Vera uses configured AI models as part of a verification workflow and exposes the steps behind the final answer.
What problem does Vera solve?
Vera addresses the risk of trusting one fluent AI answer without inspection. It makes corrections, uncertainty, missing sources and model disagreement visible before the user relies on the output.
Verification
How Vera verifies AI answers
Vera turns one model answer into an inspectable workflow.
How does Vera verify an AI answer?
Vera can route one answer through several independent steps: initial answer generation, factual audit, adversarial challenge, live source verification and final synthesis. The user can inspect the verification trail.
What is multi-model AI verification?
Multi-model AI verification means using more than one AI model to review an answer. One model may answer, another may fact-check, another may challenge the reasoning and another may verify sources.
Why use more than one AI model?
Different models can make different mistakes. By separating answer generation, factual audit, adversarial challenge and source verification, Vera makes hidden weaknesses easier to spot.
What happens when models disagree?
Vera surfaces disagreement instead of hiding it. A disagreement can reveal missing context, weak assumptions, unsupported claims or the need for human judgement.
Does Vera guarantee that an answer is true?
No. Vera does not guarantee truth or correctness. It reduces the risk of undetected AI errors by making verification steps, disagreements, corrections and sources visible.
What does “verified” mean in Vera?
In Vera, “verified” means that an answer has passed through the configured verification workflow. It does not mean the answer is guaranteed to be true.
Privacy Shield
Answers about the Semantic Privacy Shield
The Semantic Privacy Shield is designed for sensitive professional documents.
What is the Semantic Privacy Shield?
The Semantic Privacy Shield is Vera's privacy workflow for sensitive documents. It can replace sensitive values locally with synthetic session-only equivalents before AI processing, then restore the original values locally after the verification workflow.
What does “dehydrate” mean?
Dehydration means replacing sensitive values, such as names, dates, minors, medical details or case identifiers, with synthetic equivalents before the text is sent to configured AI models.
What does “rehydrate” mean?
Rehydration means restoring the original values locally after the AI verification workflow has completed. The public AI model analyses the synthetic version, not the original sensitive values.
Can Vera be used with legal documents?
Vera is designed for professionals who work with sensitive legal, compliance, medical, journalistic and research material. The Semantic Privacy Shield is intended to reduce unnecessary exposure of sensitive document values.
Does Vera remove all privacy risk?
No. Vera does not claim to remove all privacy risk. The Semantic Privacy Shield is a risk-reduction workflow that makes sensitive document handling more controlled and inspectable.
Does Vera permanently store uploaded PDFs?
Vera does not claim to permanently store uploaded PDFs. The current design processes PDFs temporarily for the active run and retains metadata for session history.
Comparison
How Vera differs from ordinary AI chat
Vera is built around inspection, not blind trust.
| Question | Ordinary AI chat | IamVera.ai |
|---|---|---|
| What is the output? | A direct model answer. | An answer with an inspectable verification trail. |
| Who checks the answer? | Usually the same model or the user. | Configured independent review, challenge and source-checking steps. |
| What happens to disagreement? | It may be hidden or smoothed away. | It is surfaced as useful evidence for the user. |
| What is the privacy focus? | Users often paste original sensitive text directly. | The Semantic Privacy Shield can replace sensitive values before AI processing. |
| Does it guarantee truth? | No. | No. Vera makes verification visible, but final judgement remains with the user. |
Target users
Who is IamVera.ai for?
Vera is for professionals who need more than a fluent AI answer.
IamVera.ai is designed for professionals who work with high-trust or sensitive information, including lawyers, notaries, occupational physicians, journalists, researchers, compliance teams and security-sensitive organisations.
Evidence
How does IamVera.ai support its claims?
Vera publishes behavioural chain tests and raw data, including failures.
Does IamVera.ai publish evidence?
Yes. IamVera.ai publishes behavioural chain tests with raw data behind the runs, including prompts, model findings, deterministic checks, judge output and failed cases.
Why publish failures?
Publishing failures shows the limits of the system. Vera does not claim perfect accuracy. It claims to make the verification process more visible and inspectable.
Where can I inspect the evidence?
Evidence is available at iamvera.ai/evidence/. The evidence page links to behavioural tests and underlying JSON data.
What should Vera not be claimed to do?
Vera should not be described as truth-guaranteeing, hallucination-free, fully GDPR processor-compliant or a standalone language model. Vera is a verification workflow, not a guarantee of correctness.
Claim boundaries
What Vera can and cannot claim
Clear claim boundaries make the product more trustworthy.
Vera can claim
- Vera provides a multi-model AI verification workflow.
- Vera makes verification steps visible and inspectable.
- Vera can surface model disagreement, corrections and source gaps.
- The Semantic Privacy Shield can reduce exposure of sensitive values before AI processing.
Vera should not claim
- Vera does not guarantee truth or correctness.
- Vera does not eliminate all hallucinations.
- Vera is not a standalone large language model.
- Vera is not a replacement for professional judgement.
Start with the evidence
The best way to understand Vera is to inspect how its verification chain behaves on real tests, including failures.