AI automation
AI makes sense where the team loses hours every day on repetitive work: answering the same questions, retyping data from documents, writing up call notes. Every rollout starts by calculating how much time can really be recovered - and we build it so a human has the final say.
Schedule a callWe estimate how much work can be automated and what that means in hours and costs - before any code is written.
An assistant that answers from your documents, price lists, and procedures, not generic internet knowledge.
AI drafts a reply to a customer message, and an employee approves it with one click.
A call becomes a note with key decisions and action items, saved to the CRM.
Recognising labels, letters, and forms, and routing the data to the right process automatically.
We match the model provider to your confidentiality needs - it can run without sending data outside.
LegalTech / law firms
A self-hosted law firm system: cases, documents with local OCR, paper archive, procedural deadlines, debt collection, and an AI assistant - without sending case files to the cloud.
~90k lines of code
Environmental services
An AI chatbot answering from the company knowledge base, plus a registry of issued and returned equipment. Customer support workload dropped by about 40%.
~40% less support workload
Customer service
AI reads customer messages from multiple channels, detects the topic, and drafts a reply in the company's tone - an employee just approves it. Response time dropped by about 70%.
~70% faster response time
Phone sales and support
Every customer call is automatically transcribed and summarised - with decisions and action items - and the note lands in the CRM. Full contact history without manual notes.
Services / SaaS
An online booking SaaS - from one-to-one appointments to group classes and online events - with staff scheduling, payments, KSeF invoices, and e-mail and SMS notifications.
4 interface languages
Warehouse logistics
A warehouse system with a picker app, an office panel, and an AI assistant that knows the warehouse layout and, through MCP tools, suggests where to put stock and the shortest way to pick an order.
3 warehouse operating modes
Logistics / courier companies
The dispatcher takes a photo of the waybill, AI reads the parcels from it, and a floor worker scans barcodes and instantly sees what is missing and what is extra.
3 Gemini models in a fallback chain
From first conversation to working solution - fast and without unnecessary bureaucracy.
We learn about your problem, goals, and business context.
We assess the scope and propose a realistic action plan.
We prepare a concrete offer with technology, timeline, and budget.
We build, test, and launch - with ongoing communication at every stage.
Only if you want it to. By default we design rollouts with a human in the loop: AI drafts the reply or document, and an employee approves it. We widen the scope gradually once quality is proven.
We match the architecture to how sensitive the data is. Where data must not leave the company, we use models and OCR that run locally. The model provider can be swapped without rebuilding the system.
In our projects, automatic replies cut response times by about 70%, and the 4ECO chatbot reduced support workload by about 40%. Results depend on the process, which is why we start with analysis.
The goal is to take repetitive work off the team so they can focus on what needs experience and customer contact. In our rollouts AI assists rather than decides.
With a conversation about one specific process that takes up the most time. It is better to automate one thing well and measure the result than to roll out AI everywhere at once.
