AI & Automation
Most companies experimenting with AI are still in the demo phase. They've seen GPT answer general questions impressively and assume the same will work for their specific documents, their specific workflows, their specific knowledge base. It won't — not without engineering. We built LawyerAI, an AI legal assistant used by law firms that processes hundreds of queries daily and cites verifiable sources. We know the gap between a prototype and a production system, and we know how to close it.
The core problem with off-the-shelf AI is that it doesn't know your business. A general model will give you general answers — useful for writing emails, useless for answering questions about your specific contracts, your product specifications, your internal procedures. The solution is Retrieval-Augmented Generation (RAG): a system where the AI searches your actual data before generating an answer, and cites the source. This is what we built for LawyerAI, and it's what we build for clients across industries.
Beyond question-answering, AI is a practical tool for automating document-heavy workflows. Contract review that used to take 2 hours takes 10 minutes. Invoice data extraction that required a data-entry employee runs automatically. Support tickets get drafted responses the agent approves with one click. These aren't theoretical — they're things we've built. The economics work because the cost of running the AI is a fraction of the labour cost it replaces.
Data security is always the first concern. We support multiple deployment options: fully on your own infrastructure (no data leaves your servers), private API endpoints with Azure OpenAI or Anthropic in your own cloud account, or anonymisation pipelines that strip sensitive data before it reaches any external model. We'll recommend the right setup based on your data sensitivity and infrastructure constraints.
- RAG systems — AI that searches and cites your own documents and data
- AI chatbots and assistants trained on your knowledge base
- Document analysis: contracts, invoices, forms — structured extraction
- Automated workflow triggers based on AI-classified inputs
- OpenAI GPT-4o and Anthropic Claude integration
- On-premise deployment option (no data leaves your servers)
- Fine-tuning and custom model training for specialised domains
- Evaluation and testing pipelines to measure accuracy
- Integration with your existing CRM, ERP, or document management system
Through RAG (Retrieval-Augmented Generation). Before generating an answer, the system searches your documents for relevant passages and provides them to the model as context. The model then answers based on what it found — and we include the source reference so you can verify. This approach dramatically reduces hallucinations compared to prompting a general model.
We offer three deployment options based on your data sensitivity: (1) fully on-premise — the model runs on your server, nothing leaves your network; (2) private cloud — your own Azure OpenAI or Anthropic deployment in your cloud account, data stays in your region; (3) anonymisation pipeline — sensitive fields are stripped or replaced before reaching any external API. We'll recommend the right option for your use case.
Yes. We built LawyerAI — an AI legal research assistant used by law firms in the Czech Republic. It processes hundreds of queries daily, cites sources from Czech and European legal databases, and runs with high availability in production. This isn't an agency that read about RAG last month.
A prototype. Before committing to full development, we build a working prototype on a sample of your data, measure accuracy against real queries, and show you the results. You decide whether the accuracy is good enough to justify the investment. We don't start full projects that might not work.
We calculate it with you before starting. Identify the task, measure current time cost (hours × wage), estimate the AI's throughput and accuracy, and model the economics. The payback period for most document processing and classification projects is under 6 months.
Yes. AI doesn't need to be a standalone tool — we integrate it into your CRM, document management system, support platform, or whatever workflow it's automating. The AI layer becomes part of your existing process, not a separate thing people have to remember to use.
AI and automation projects often qualify for EU digitization grants (OP TAK in CZ, Recovery Plan funds in SK). Coverage can reach 30–50% of eligible costs. We'll help you assess eligibility before the project begins — it's worth checking.
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