Every AI output, verified — from financial reports to chatbot replies and agentic data bots.
The independent trust layer for AI in regulated, high-stakes work — from financial reporting to support chatbots and agentic knowledge and data bots.
One call after generation returns each factual claim as verified, disputed, or unverifiable, with confidence and the exact source reference.
Deploys from Azure Marketplace into your own infrastructure. An MCP connector for ChatGPT, Claude Code, and Copilot is on the way.
AI-generated draft
Comments on the third quarter
Net sales increased 9.2 per centWrong number. The Q3 report shows growth of 6.1 per cent, not 9.2. Suggested correction: 6.1 per cent. to SEK 1,840 million (1,734). Growth was driven by the Pharmacy segment, up 14 per cent on higher prescription volumes, and by continued recovery in the Norwegian market, while grocery volumes remained flat. The EBITDA margin improved to 21.3 per cent (19.8), mainly reflecting lower logistics costs following the warehouse consolidation.Unsupported. Not found in the sources provided. Ask for a source or remove it.The challenge
Your AI sounds right. Sometimes it isn't.
Language models state figures, policy terms, and explanations that look plausible but aren't in your data. In a board report or a customer answer, that's an incident. So your people re-check everything by hand, and for high-risk systems the EU AI Act expects that oversight to be documented.
VeriVeri catches what the AI made up, shows the evidence, and logs every check.
The business case — what it puts on your P&L
And the line a spreadsheet won't show: independent verification is what lets sensitive processes, regulated functions, and entire business lines move onto AI in the first place — the transformation that stays off the table until the output can be trusted.
Green impact
Verification that doesn't cost the earth.
VeriVeri checks claims with models sized to the task, not a frontier model on every sentence — roughly 10× less CO₂ per check than verifying with frontier-scale models. Trustworthy AI you can defend on sustainability reporting, not just accuracy.
How it works
Two inputs. Every claim checked.
Send the AI-generated text and the sources it has to be true to. VeriVeri returns a verdict and a suggested fix for every claim — so a person reviews about one in a hundred, instead of all of them. Any model, any provider.
AI-generated text
A report draft, a chatbot reply, an agent's answer.
Your sources
Financial statements, prior reports, research data, policies — the truth it must match.
Every factual claim checked against your sources, with confidence and evidence.
Every claim, with a verdict
Verified, disputed, or unverifiable — each with its source and a suggested correction.
A person reviews roughly one claim in a hundred. VeriVeri clears the rest automatically, and logs every check.
terms-of-service-v3.1.pdf §4.2
Catch the wrong answer before it is sent.
Your chatbot can still get it wrong. VeriVeri checks each reply against your documents before it goes out.
- Runs synchronously between generation and delivery
- Disputed claims return the contradiction and the source
- Auto-correct or route to a human; you set the threshold
- Every check is logged to the audit trail
Near real-time for conversational agents and chatbots, so a reply can be checked before it is sent; asynchronous for full documents like financial reports. You set the latency and throughput targets for your workload.
An independent check, by design
Verification, kept separate from generation.
Asking a model to grade its own work is not a control. VeriVeri writes nothing and has no stake in defending the text: each claim is checked by multi-model consensus across providers, with the evidence attached.
That separation is what unlocks the full potential of LLMs in regulated areas. You can put generation to work on processes you would never hand to an unchecked model, because the control sits outside the model that produced the output.
Where verification goes next: banking and pharmacy evaluation sets are in development with design partners. If that's your domain, you'll shape what we evaluate against.
Deployment
Runs where your data lives.
You decide where data is processed. VeriVeri deploys into your infrastructure and consumes models only in compliant regions — in the cloud you choose, or fully on-premise.
Azure Marketplace
Deploy into your own Azure tenant. Your data stays within your infrastructure.
AWS & Google Cloud
Listings for AWS and Google Cloud are in the works.
MCP connector
An MCP connector brings verification into ChatGPT, Claude Code, and Copilot.
Talk to us about a specific cloud provider or region, or about running VeriVeri fully air-gapped in your own on-premise infrastructure. Contact us for current availability.
Audit, control & reporting
Built for regulated and high-stakes business.
Auditors, internal control, consultants, and CFOs get their evidence without a project: audit traces, control data points, and reporting, out of the box. Every verification is logged with a retention window you set and masking rules you define.
Audit trails
Every verification logged — text, sources, verdicts, and confidence — with custom retention and customisable masking. The trace your auditors ask for, by default.
Control data points
Usage, verification statistics, and claim-distribution monitoring — the data points internal control and consultants pull from directly.
Compliance reporting
Audit traces and control evidence packaged for regulators, internal audit, and CFO sign-off.
Security
Security and data handling.
This is where we stand on the standards and laws that matter, and how VeriVeri already supports them. Where PII or business risk is involved, we get on a call and work through your specific industry, geography, and case.
| ISO 42001 | AI management system | IN PROGRESS |
|---|---|---|
| ISO 27001 | Information security | IN PROGRESS |
| SOC 2 Type II | Security & availability | IN PROGRESS |
| GDPR | Processor under a standard DPA; data processed in the region you choose | IN PLACE |
| EU AI Act | Supports accuracy and human-oversight obligations on high-risk AI systems; VeriVeri is not itself a decision-making system | POSITION DOCUMENTED |
- Not used for training. Source documents and AI outputs are processed for verification only.
- Data residency you choose. Processing and storage stay in the compliant region you select; fully air-gapped on-premise deployment is available.
- Encryption in transit (TLS 1.2+) and at rest.
- Retention you control. Verification payloads follow your configured retention window; audit metadata kept per plan.
- Subprocessors listed. Full register in the DPA, including model providers.
PII or business risk in scope? We'll get on a call and work through your specific industry, geography, and case before anything goes near production. Talk to our team.
For developers & technical owners
Verify and control with an API call.
One synchronous call, any model, plain JSON over HTTPS. What a technical owner actually weighs is the rest — where it runs, what it does with your data, and whether the output is something you can build control logic on.
- Drops in, no re-architecting. One call after your existing model, any provider. No lock-in to ours.
- Runs inside your boundary. Your cloud, your region, or fully air-gapped on-premise — data never has to leave.
- Never trains on your data. Processed for verification only, with retention and masking you control.
- Output you can gate on. A deterministic verdict, confidence, and source per claim — programmable, not a chat box.
// request — the source of truth + the AI text to check
{
"context": "Q3 2025 interim report. Net sales for the third quarter amounted to SEK 1,840.2m (1,734.0), up 6.1% year on year. EBITDA margin improved to 21.3% (19.8)…", // + 14 more pages of source data
"text": "In the third quarter, net sales rose 9.2% to SEK 1.84bn, lifting the EBITDA margin to 21.3% and driving order intake to a record level across the Nordic segment…", // AI-drafted board summary, ~1,200 words in full
"domain": "finance"
}
// response — every claim checked; only the problems come back
{
"request_id": "req_161128af8542",
"verdict": "wrong",
"issues": [{
"quote": "net sales rose 9.2% to SEK 1.84bn",
"explanation": "CONTEXT reports 6.1% year-on-year growth, not 9.2%.",
"proposed_fix": "net sales rose 6.1% to SEK 1.84bn",
"severity": "wrong"
}],
"cost_usd": 0.005052
}Build vs. buy
Building this in-house is a 12–18 month project.
A verified, audit-grade checking layer is years of evaluation, security, and upkeep to own. Or you turn VeriVeri on.
See the full comparisonFrom the field
Deployment notes from inside regulated industries — what breaks, what scales, and what we built VeriVeri to fix.
Your AI is only as valuable as your ability to trust it.
“The technology scales. Your trust process does not.”
How deploying generative AI across banking, pharmacy, and grocery at one of Sweden's largest retail groups revealed a universal bottleneck — and why we built VeriVeri to eliminate it.
Read the full storyFAQ
Common questions.
How fast is verification? Can it run inline?
Yes. For conversational agents and chatbots it runs in near real time, so a reply can be checked before it is sent. For full documents like financial reports it runs asynchronously. You set the latency and throughput targets for your workload.
How accurate is it, and how do you measure that?
We track per-verdict precision and recall against domain datasets, deepest in financial reporting. The evaluation summary is available under NDA.
How do I provide my source data?
Per request: inline documents or references to registered sources. Claims are checked only against what you provide.
Do we have to build an integration to use it?
No. Deploy from Azure Marketplace into your own tenant, or use the MCP connector for ChatGPT, Claude Code, and Copilot when it ships. The API is there when you want a custom integration.
Is my data used to train models?
No. Documents and outputs are processed for verification only. The DPA lists every subprocessor that touches your data.
Where does processing happen? Can we deploy on-premise?
Processing and storage stay in the EU. On-premise deployment is available on Enterprise.
Are you tied to a specific model provider?
No. VeriVeri verifies output from any model; its own checks run as multi-model consensus across providers.
What happens in the 30-minute demo?
We run VeriVeri on a sample document, walk through the verdicts and the API response, and cover how the design-partner arrangement works. You receive the documentation pack afterwards.
What does the private beta mean for us, concretely?
VeriVeri is in private beta. We work with a small number of design partners who run it on their own documents, with direct access to the founder and a say in what we evaluate next.
Get started
Get in touch.
Tell us about your use case and we’ll get back to you — whether you’re evaluating VeriVeri or ready to integrate.
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