AI and data pipelines that deliver real engineering value
Custom AI agents, Azure OpenAI integrations, and data warehouses — with guardrails, measurable outcomes, and no hype.
What we deliver
We help teams adopt AI pragmatically — from Microsoft Fabric data warehouses and TimescaleDB pipelines to Azure OpenAI agents that automate real engineering work.
Data warehouse and analytics platform
Microsoft Fabric, TimescaleDB, or custom PostgreSQL-based pipelines. Centralised data from heterogeneous sources, automated ETL, and real-time reporting.
Custom AI agents
Azure OpenAI-powered agents for automating repetitive work — code review, document processing, internal reporting, or customer-facing tooling.
Azure OpenAI integration
Connect to Azure OpenAI Service, build a RAG pipeline over your proprietary data, secure model access, and optimise inference costs.
AI tooling for engineering teams
GitHub Copilot and Cursor deployment with guardrails and team onboarding. Measurable productivity improvements — not just a new tool that nobody uses.
Magistra a.s. — Pharmacy chain data platform
Microsoft Fabric data warehouse integrating 200+ pharmacies. Automated ETL pipelines replacing manual exports. Real-time reporting and 360° customer view across all channels.
When to reach out
Data is siloed — reporting is manual and slow
Business decisions rely on spreadsheets and manual exports. You need a central data platform with automated pipelines and real-time dashboards.
High-volume data processing at GB/s
Network telemetry, IoT data, or transaction streams — you need a storage and query layer that holds up under real enterprise volumes.
You want AI to reduce repetitive engineering work
Code review, documentation, test generation — measurable time savings with proper guardrails, not a chatbot bolted on the side.
Technologies
- Microsoft Fabric
- TimescaleDB
- PostgreSQL
- Azure OpenAI
- GitHub Copilot
- Semantic Kernel
- RAG
- pgvector
- Azure AI Search
- Python
- Power BI
Related reading
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Claude Batch API for translations: 50% cheaper, but it's a queue
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MCP servers and Claude: five questions we answer before writing a line of code
Model Context Protocol is a hot topic. Wiring Claude to a database, however, doesn't make a product. After several prototypes, we use a five-question methodology before a single line of MCP server code gets written — plus one uncomfortable question about admin UIs.
More services
Build systems that scale — without bottlenecks
We design and deliver .NET cloud applications from API architecture to production. Clean code, reliable integrations, zero surprises under load.
Azure infrastructure that works — and does not overspend
Architecture, migration, and optimisation of your Azure environment. Concrete outcomes measured in performance and cost — not just slides.
Ship changes daily — without the anxiety
Automated pipelines, observability, and release management. Deployments become a routine — not a weekly fire drill.
Book a 30-min consultation with a senior architect
No commitment. No sales pressure. Direct technical conversation.