AI agents for operational tasks
Agents that complete tasks on their own: capturing orders, preparing quotes, handling tickets, reconciling data. With clear rules and approvals.
AI agents & AI engineering
AI agents that genuinely work alongside your team.
From knowledge assistants to agents that take over operational tasks: we build AI solutions on top of your company knowledge, in text and voice, and connect them to your systems via MCP and APIs. Secure, traceable and under your control.
- RAG on your company data
- Voice & text assistants
- MCP integration
What we build
Everything AI, tailored to your business
Not a gimmick, but AI embedded in your processes that measurably takes work off your hands.
Company knowledge base (RAG)
Your manuals, policies, product data and contracts as searchable knowledge. The assistant answers with sources instead of guessing.
Chat & support bots
High-performance bots for your website, customer portal or intranet, based on your own knowledge and available around the clock.
Voice assistants
Assistants that speak and listen: phone reception, appointment booking, order intake or voice control in the warehouse and field.
MCP servers & tool integration
Through the Model Context Protocol (MCP) and APIs, agents work directly with your ERP, CRM, shop, ticket system or database.
Document AI
Automatically recognize, extract, check and import invoices, delivery notes, forms and emails into your systems.
AI workflow automation
Multi-step processes in which AI, your software and your team work together, including escalation to humans when it matters.
AI in your software
AI features right inside your apps, portals and shops: smart search, product configurators, text generation, summaries and forecasts.
From chatbot to agent
Three levels, you set the pace
Many companies start with an assistant and give the AI more responsibility step by step.
- 01Assistant
Answers questions based on your company knowledge, in text or voice.
e.g. "Which warranty applies to product X?"
- 02Copilot
Prepares work; a human reviews and decides.
e.g. a draft quote from a customer inquiry
- 03Agent
Completes tasks on its own in your systems, with defined rights and approvals.
e.g. creating an ERP order from an email
Use cases
Where AI agents save time right away
24/7 customer service
Answer common questions, order status and complaints automatically and hand complex cases over cleanly to your team.
Processing emails & orders
Recognize incoming requests, extract data and create orders, tickets or contacts directly.
Internal knowledge search
Employees ask in plain language and get answers from manuals, processes and project documents.
Phone & appointment assistant
Take calls, record requests, book appointments and organize callbacks.
Reports on demand
"How did revenue develop in October per branch?" The agent queries your data and delivers the answer with a table.
Quotes & documents
Prepare quotes, reports and minutes automatically from your templates and data.
Secure & controlled
AI you can trust
An agent working inside your systems needs clear boundaries. We build security and traceability in from the start.
- ✓Your data under control
GDPR-compliant data protection, EU AI Act requirements taken into account, and clear rules on which data the model may see.
- ✓Free choice of model
Leading cloud models or open-source models, operated in the EU or in your own infrastructure on request.
- ✓Roles & permissions
An agent only sees and does what its role allows. Critical actions require human approval.
- ✓Measurable quality
We systematically test answers against real cases to minimize hallucinations, and monitor quality and costs in operation.
- ✓Traceable
Every answer and every action is logged. You can always see what the agent did and why.
Our approach
From use case to production agent
Start small, test with real data, then expand.
- 01Use case workshopWe identify the tasks where AI delivers the most value and clarify data, systems and boundaries.
- 02PrototypeA working prototype with your real data shows early on what is possible.
- 03Integration & safeguardsConnection via MCP and APIs, roles, approvals, tests and logging.
- 04Operation & improvementMonitoring of quality and costs, team training and continuous development.
FAQ
Questions about AI agents
What is the difference between a chatbot and an AI agent?
A chatbot answers questions. An AI agent can also act: it uses tools and interfaces, creates records, sends messages or triggers processes, always within the rights you give it.
What does RAG mean?
Retrieval-augmented generation. Before the AI answers, it searches for the relevant passages in your own documents and data. Answers are based on your company knowledge, up to date and traceable to a source.
What is MCP?
The Model Context Protocol is an open standard that lets AI models talk securely to tools and systems. We build MCP servers for your software so agents can read and work there in a controlled way.
Does our data stay with us?
We decide that together. Options include cloud models with contracts that exclude training on your data, hosting in the EU, or self-hosted open-source models in your infrastructure.
What if the AI gives a wrong answer?
We reduce the risk through RAG with sources, clear boundaries, tests with real cases and approvals for critical actions. In operation we monitor quality continuously and keep improving.
Does it work with our existing software?
In most cases, yes. Via APIs, database connections or MCP servers we connect agents to ERP, CRM, shop, ticket systems and custom software. If an interface is missing, we build it.
How do we best get started?
With a concrete use case that costs a lot of time today. We assess it in a workshop, build a prototype with your real data, and then decide together how to expand.
Your first agent
Which task should AI take over in your company?
Describe a process that costs a lot of time today. In a free call we'll show you what an AI agent for it could look like.