The platform every other AI project stands on: model gateway, retrieval, caching, cost control, evaluation and observability, running somewhere you control.
I build the layer that makes AI actually usable in a company: the infrastructure, the agents and the assistants people can talk to. I work as an independent consultant from Bratislava, mostly with engineering teams that already have an idea and need someone who can tell them — honestly — what will hold up in production.
My work splits into three layers. AI infrastructure is the platform underneath: model routing, retrieval, caching, evaluation, observability and cost control. AI agents are the systems that use that platform to do multi-step work — reading a CRM, drafting a contract change, reconciling an invoice — with humans approving the parts that matter. AI chatbots on websites are the customer-facing version of the same stack: multilingual, grounded in your own content, and instrumented so you can prove whether they earn their keep.
Before this I spent a decade on conventional software: enterprise platforms at BSS PRAHA, a content platform and public API at Audioline, and battery diagnostics at BatteryCheck. That background is the reason my AI work survives contact with a real IT department. Retrieval needs a database, agents need permissions, a chatbot needs a deploy pipeline — I have built all of those without a framework in sight.
I work in English, Czech and Slovak, and I deliver in all three. Most engagements start with a two-week audit: I read your systems, your data and your constraints, and you get a written plan with costs — whether or not you hire me for the next phase.
Based in Bratislava, Slovakia. Working with clients across the EU, mostly remote.
What I do
Six services, one stack underneath. Start anywhere — most engagements combine two or three.
Multi-step systems that act inside your tools — CRM, ERP, ticketing, documents — with permissions, budgets, audit trails and human approval where it counts.
Assistants grounded in your real content that answer, qualify, hand off to a human and report what they actually resolved.
The retrieval layer: chunking, embeddings, hybrid search, reranking, freshness and citations — so answers stay correct when the documents change.
Golden datasets, LLM-as-judge, regression suites and dashboards for quality, latency and spend — so you can change models without gambling.
The non-AI half: APIs, integrations, internal tools, IoT and web platforms, built to outlast the current framework trend.
Selected work
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BSS PRAHA
Long-running internal platform work: multi-tenant services, integrations and data pipelines for enterprise customers.
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Audioline
Content platform and public API rebuilt around typed contracts, caching and predictable latency.
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BatteryCheck
Battery diagnostics for fleets and workshops — device fleet management, telemetry ingestion and reporting.
News
- 2026 Focused on AI infrastructure for regulated enterprise environments
- 2026 Shipping multilingual website assistants for EN / CS / SK sites
- 2025 Moved full-time onto AI agents, retrieval systems and LLM platform work
- 2025 Rebuilt retrieval infrastructure with hybrid search and reranking
- 2024 Delivered enterprise integrations and typed API platforms
- 2023 BatteryCheck shipped: battery diagnostics at fleet scale
