AI Engineering
In AI we actively use the latest tools and choose between locally deployed models and frontier models from leading providers based on each customer's specific needs. We balance data security, latency, cost and output quality so the solution fits real processes - not generic templates.
Examples of AI in practice

Processing accounting documents
For an accounting firm we designed a system that automatically extracts data from invoices, statements and scans, assigns it to the correct accounts and prepares materials for review. We store internal guidelines and client history in a vector database so the assistant can quickly find context without manual browsing. Personal data and sensitive items are processed by a local model directly in the client's infrastructure; only anonymised data is sent to the cloud.
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Personal assistant
For a growing e-commerce company we built a personal assistant for the technical team. It monitors cloud service usage, alerts on security risks and suggests operational cost savings. AI agents continuously check configuration, summarise incidents and prepare decision materials - without having to manually go through dozens of dashboards every week.
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