AI automation and autonomous agents
AI automation with measurable results — not flashy demos.
AI has become a marketing word. Everyone sells "AI transformation" — few deliver automation that works in production and concretely reduces costs or time. For us, AI is not a technology — it's a tool: any process with high volume and repetitive steps is a candidate, and everything is measured in hours saved and accuracy.
If at least three of these sound familiar, it's time to talk.
Teams manually processing hundreds of invoices, contracts, forms, reports — month after month
Customer support saturated with repetitive questions
Fragmented inter-departmental processes with no orchestration
Data scattered across Excel, email and legacy systems — no source of truth
Failed AI projects because there was no quality data or no clear KPIs
We start with a discovery process: identifying 3-5 automation candidates with the best effort/impact ratio. We quantify: how many hours are spent today, what % can realistically be automated, what's the monthly ROI.
We build a pilot for the highest-ROI case — in 4-8 weeks. We use proven stacks: OpenAI GPT-4o / Claude for reasoning, n8n / Make / Zapier for orchestration, vector DBs (Pinecone, Qdrant) for retrieval, Python for custom logic.
The pilot runs in parallel with the manual process for 2-4 weeks for validation. Only after metrics demonstrate value do we scale. We never build "on faith".
Process, data, infrastructure assessment. Roadmap of automation candidates with estimated ROI.
Document processing, customer support, sales qualification, content generation — integrated with your systems.
Internal chatbot answering from your knowledge base (procedures, manuals, contracts) — with source citations.
Flow orchestration between email, CRM, ERP, Slack, Excel — no-code, scalable.
Usage policies, data leakage prevention, audit logging, EU AI Act compliance.
How to use ChatGPT/Claude in daily work — productivity +30-50% for white-collar.
Workshop with your team. List of automation candidates prioritised by ROI.
4-8 weeks. Implementation on the first case, parallel run with the manual process.
Time, accuracy, user satisfaction measurement. GO/NO-GO decision based on metrics.
After validated pilot: rollout to other cases, extended integrations, production monitoring.
Continuous adjustments based on feedback, drift monitoring, model updates.
You pay for quantified results (hours saved, errors reduced) — not promises.
We use open technologies — no vendor lock-in.
Small initial investment (4-8 weeks), scaling decision based on real data.
EU AI Act, GDPR, data rights — built in from design, not bolted on.
30 minutes — we explore what you have, what's missing and what concrete next steps look like.
