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Česky
We help companies find real use-cases for AI and ship them into production. Agentic workflows, document extraction pipelines, retrieval over your own data, evaluation harnesses you can defend. No demo videos. Real systems your team operates.
I want AI in my businessAnyone can stand up a Claude API call. Almost no one ships AI that holds up under real traffic, real data, and real people. That last 80% is where the work is: evaluation harnesses, drift monitoring, fall-back behaviour, cost ceilings, PII handling, audit trails. We've shipped that 80% across a dozen sectors — and we'd rather hand you the playbook than sell you a perpetual support contract.
Triage 4,000 weekly support tickets into seven categories with auto-routing.
Read inbound RFP PDFs, extract key dates & commitments, draft a response.
Run a retrieval agent over five years of board minutes for governance review.
Match free-text invoice line items to a 12,000-row product catalogue.
Conversational assistants for first-line customer contact and self-service support. Built on RAG with citations and operator escalation when answer confidence drops.
Invoices, orders, contracts, email inquiries, automated reports. OCR + LLM pipelines with confidence scoring and an audit trail — not ad-hoc scripts.
Sales forecasting, predictive maintenance, employee-attrition prediction, financial outlooks. We pick the approach based on where the signal actually lives in the data.
Product recommendations for e-commerce, campaign targeting, dynamic pricing based on customer behaviour. A/B tests and legible segments instead of a black box.
Fraud, phishing, anomalous network access, early catches of unusual operational events. An amplifier for your SOC team — not a replacement.
Route planning, vehicle utilisation, inventory optimisation, just-in-time production. A mix of classical optimisation (OR-Tools) and AI for parameter estimation.
Voice agents in call centres, voice control in banking, telecoms, and e-commerce. Realistic expectations for latency, background noise, and language variants.
Marketing copy drafts, developer-assist coding, design-draft generation. The key isn't the model — it's the evaluation harness. Without it, you can't defend quality.
Defect detection in manufacturing, visual QA, image classification and OCR. We deploy at the edge near the production line or in the cloud — depending on data sensitivity.
A two-week audit of your workflows, data, and tools — surfacing the highest-ROI places where AI moves the needle (and the places it won't).
Multi-step agents that plan, execute, and self-correct. Tool-calling, MCP-aware, with human-in-the-loop checkpoints where stakes are high.
RAG done well — chunking that respects your document structure, hybrid search, citation-grade outputs your legal team will sign off on.
Eval harnesses that catch regressions before they ship. Cost ceilings, prompt-injection defences, fallback behaviour you can explain.
PII handling, data residency, audit trails, GDPR and NIS2. Where data flows, who can see it, and what you can prove about it after the fact.
We integrate into your existing stack and stay long enough to teach your team to operate it. Not a Jupyter notebook. Not a perpetual dependency.
We don't ship "AI features" because the marketing team wants a checkbox. We don't build chatbots that just summarise a website. We don't take on projects where the data is garbage and "AI will fix it" — that's still a data project with extra steps.
We do build systems where AI replaces or accelerates a process you can describe in concrete terms, with success criteria you can measure.
Frontier closed models for the heavy lifting (Claude, GPT, Gemini), open-weights for cost-sensitive paths (Llama, Qwen, the latest Mistrals), small specialist models for narrow tasks. We pick what fits, not what's hyped.
Hosting on Azure OpenAI, Anthropic API direct, Bedrock, or self-hosted on your infrastructure. Whatever the data residency story demands.