AI for banks, insurers and healthcare with regulatory rules, audit logs and on-prem setup
We build AI systems that pass security review and compliance: data stays in your perimeter, every agent action is logged, and regulatory rules live in the code, not only in the prompt.
What hurts
The business wants a voice agent or call analytics, but security blocks any cloud service. The project spends months in approvals and never starts.
The regulator sets rules such as permitted call hours and banned phrasing in debt collection. If the bot breaks them even once, the fine and the inspection come to you.
The auditor asks who saw a customer record and when, and why the system made a decision. Typical AI products cannot answer that.
What we build
- Analysis of regulatory requirements and internal policies with your compliance team
- An architecture deployed in your perimeter or on a dedicated server
- A private LLM on vLLM so data never reaches third-party models
- Regulatory rules in code: schedules, limits, banned topics and phrasing
- An audit log of every agent action and data access
- Role-based access and integration with your CRM or core banking system
- A scenario test suite, including rule violations
- Launch on part of the customer base first, with manual control
What you get
- A working AI system in your perimeter, with source code
- Audit logs and compliance reports
- A documentation pack for security review and auditors
- A test suite that checks regulatory rules
- Training for operators and owners
How we measure the result
- Number of regulatory rule breaches found by tests and in production
- Share of agent actions fully recorded in the audit log
- Time to answer an auditor request
- The business metric written into the contract, such as resolved case share
Systems and stack
Industries
Questions
Do you have experience with banks?
Yes. For IdeaBank we built a voice agent for overdue debt collection under National Bank of Ukraine rules, with results flowing into the bank CRM. For call analysis we run our own LLM on vLLM on our servers, so data does not go to third-party models. Project details are shared within the limits of the NDA.
How much does it cost and how long does it take?
From $10,000, usually 8–14 weeks. In regulated industries more time goes into approvals, testing and documentation than into code. The price depends on the number of integrations, deployment requirements and documentation scope.
Do you guarantee the system will pass a regulatory review?
No, and nobody can honestly guarantee that. We build to the requirements we agree with your compliance team and counsel at the start, and we prepare evidence that they are met. Compliance is decided by the regulator or auditor.
Why should we trust you with access?
We hold ISO/IEC 27001:2022 certificate No. 4160097. We sign an NDA and a GDPR DPA before any access. We work with least privilege, through your VPN and only on the data the task needs.
What if the AI makes a mistake?
AI sometimes makes mistakes, so critical rules are enforced in code, not only in the prompt. The agent hands disputed cases to a person. Every action is logged, so an error can be traced and reviewed.
What happens after launch?
Support under an SLA with monitoring, updates and incident response. Regulatory rule changes go in together with tests. Or we hand the system to your team with documentation.
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Describe the task. We reply within one business day, the first call is with the founder.
Describe the task. The first call is with the founder.
We reply within one business day. 30 minutes to tell you whether it is worth doing and what it costs.