The bottleneck
You want to move fast with AI. Chatbots, agents, report generation — the technology is ready. But every deployment hits the same wall: proving the output is trustworthy. Your AI drafts a report in minutes. Your team spends hours verifying it. Your AI answers a customer in seconds. Your reviewers spend days proving it’s safe to go live. And when you switch models or add a new use case, you start from scratch.
The technology scales. Your trust process does not.
VeriVeri — how it works
A verification gate between any AI system and its output — checking generated content against your ground truth before it reaches a customer, a decision-maker, or the next step in an autonomous workflow.
Chatbots
Every response verified against your approved knowledge base before the customer sees it. No hallucinations reaching production.
AI agents
Autonomous workflows where each step is verified against business rules and source data — enabling true automation, not just assisted manual work.
Report generation
AI-drafted financial analyses, compliance reports, and assessments checked claim-by-claim against underlying data. Audit-grade confidence at AI speed.
Model change management
Swap models, upgrade versions, mix providers — VeriVeri verifies the output regardless of what generated it. The cost of change drops dramatically.
The business case
VeriVeri turns AI trust from a project-by-project cost into reusable infrastructure. Deploy faster. Scale wider. Change models without fear.
Financial reports, internal controls, regulatory filings — every draft triggers rounds of manual fact-checking. VeriVeri verifies continuously as the report evolves, catching errors at every iteration. Teams move from draft to trusted output in days instead of weeks.
Before any AI solution goes live, data scientists, software engineers, and business domain experts spend weeks testing and validating outputs. Multiply by every use case in your pipeline. VeriVeri compresses this from weeks to hours.
Compliance is not a one-time gate — it’s infrastructure. VeriVeri creates a verification layer that logs what was checked, when, and against what ground truth. Every output, every time. Not a sample. Not a quarterly audit. Continuous and auditable by design.
With VeriVeri, and without
Without VeriVeri
- Each AI use case needs its own trust process
- Model upgrades require re-testing everything
- Scaling AI means scaling manual review teams
- AI stays in pilot — too risky for production
- Model choices blocked by risk teams
With VeriVeri
- One verification layer covers all use cases
- Swap models freely — the gate catches errors regardless
- Add new AI use cases without rebuilding trust from scratch
- AI reaches production faster — trust is automated
- Use the best model for the job — verification is the safety net
Why we’re building this
VeriVeri’s founder led the generative AI transformation of customer service at one of Sweden’s largest retail groups — spanning banking, pharmacy, and grocery retail. Three regulated domains where accuracy is not optional. The program was the first of its kind in Europe, recognized in a Microsoft customer story. The core lesson from deploying GenAI at scale in regulated environments: the bottleneck is never the technology — it is proving the output is trustworthy. Every domain required its own test datasets, labeled ground truth, evaluation pipelines, and manual review cycles — built from scratch, rebuilt with every model change. That is the problem VeriVeri eliminates.
VeriVeri’s verification approach is not limited to customer service. It applies wherever AI-generated content must be accurate against source data — internal control and audit reporting, financial analysis, regulatory filings, or conversational analytics where users talk to their data. The pattern is the same: generate, verify against ground truth, trust the output.
Design partner program
We’re co-developing VeriVeri with companies who feel this problem daily. Bring a real use case. Get VeriVeri configured to your workflow.
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