AI & Process Automation

We turn AI models into concrete results: assistants that answer customers, agents that automate repetitive work, and solutions that search intelligently across your documents. We integrate the best models on the market.

What we do

Applied AI, not hype

AI only becomes valuable when it solves a real problem: a shorter response time, less manual work, better decisions. We identify where AI delivers ROI in your business, choose the right model (cloud or self-hosted, for sensitive data) and integrate it securely into your existing workflows.

Assistants

Chatbots & AI assistants

Assistants for customers and internal teams, integrated with your website, WhatsApp or your apps.

RAG

Intelligent document search

Precise answers based on your own documents, contracts and procedures, with source citation.

Agents

AI agents & automation

Agents that execute tasks: classify emails, fill in data, generate reports and trigger workflows.

Content

Content generation & processing

Generating, summarising and translating text, extracting data from documents and images.

Privacy

AI with private data

Self-hosted solutions or local models, for cases where data cannot leave the organisation.

Integration

Integration into existing flows

We connect AI to your CRM, ERP, email and apps via API, without changing the way you work.

Real results

Case studies

Anonymised examples from delivered projects. Client names are confidential.

BEBelgiumLegal services

A legal assistant that searches the entire archive

Challenge

Lawyers spent hours searching for clauses and precedents across thousands of contracts and documents. The knowledge lived in people's heads and in folders, hard to find and impossible to scale.

Solution

We built a RAG assistant over the internal archive: documents are indexed in a vector database, and the Claude model answers questions citing the exact source and page. Access is role-controlled, and the data never leaves the client's infrastructure.

Outcome

As the archive grows, the assistant becomes ever more valuable, with no additional organising effort. Lawyers spend more time on substantive work and less on searching, and new colleagues become productive much faster, with instant access to the firm's accumulated knowledge.

Technologies used
  • Anthropic Claude
  • RAG (embeddings)
  • pgvector / PostgreSQL
  • Python
  • OCR
  • RBAC
Results at 3–6 months

Measured impact

-80%
time spent searching documents and contracts
12,000+
documents indexed and queryable in natural language
100%
answers with source citation, verifiable

“I find in 10 seconds what used to take me half a day.”

MEMiddle EastOnline retail

Automated 24/7 support, in multiple languages

Challenge

The support team was overwhelmed by repetitive questions — "where is my order?", "how do I return this?" — in multiple languages and at all hours. Response times kept rising, and so did costs.

Solution

We deployed a multilingual AI chatbot, integrated directly with the order system, which answers based on the customer's real data and escalates to a human agent when needed. Conversations are analysed for continuous improvement.

Outcome

The volume of support handled automatically kept growing as the model learned from conversations. The human team could refocus on complex cases and sales, while customers get instant answers, in their own language, at any hour — a clear advantage over the competition.

Technologies used
  • OpenAI GPT-4o
  • Multilingual NLP
  • Order API (webhook)
  • Node.js
  • Live agent handoff
Results at 3–6 months

Measured impact

62%
requests fully resolved automatically, without an agent
24/7
availability, in every supported language
+18 pts
customer satisfaction score (CSAT)

“The team now handles only the cases that truly need a human.”

RORomaniaAccounting

Invoices processed by an AI agent

Challenge

Data from incoming invoices was entered manually into the ERP — slow, monotonous and error-prone, with errors that then had to be hunted down and corrected. Volume was growing, but the team could not keep up.

Solution

We built an AI agent that reads invoices (PDF or scanned), extracts the relevant data, validates it against accounting rules and suppliers, and prepares it for import into the ERP. Unclear cases are sent for human review.

Outcome

The peak season, which used to require overtime, became manageable with the same team. The AI agent takes over the repetitive volume, while accountants focus on review and on value-added advisory work for clients, turning an operational cost into a competitive advantage.

Technologies used
  • Anthropic Claude / Mistral
  • Azure Document Intelligence (OCR)
  • Python
  • ERP API
  • Validation rules
Results at 3–6 months

Measured impact

5x
invoice processing speed
-95%
data entry errors
< 4 months
return on investment (ROI)

“People now review instead of typing invoices all day.”

Where could AI cut down your workload?

Let's identify a high-impact use case and put it into practice.

Discuss an AI project