AI Agents
AI agents that work for your business.
We build custom AI agents — autonomous assistants with tool access, memory, and real decision-making. No toy builders, no prompt hacks. Agents that understand your systems and get work done on their own.
Book a callWhat we offer
Customer Service Agents
AI agents that handle customer inquiries end-to-end — with access to your knowledge base, CRM, and ticketing system. Qualified answers, seamless handoff to humans when needed.
Voice Agents
Speaking AI agents for phone support, appointment scheduling, and qualification calls. Real-time voice processing with Pipecat, ElevenLabs, and modern LLMs.
Tool Use & Function Calling
Agents that autonomously operate APIs, databases, and your internal tools. Research, booking, data reconciliation — with clearly defined permissions and boundaries.
Memory & Context
Agents with persistent memory — vector databases for long-term context, session memory for ongoing conversations. Your agent never forgets what matters.
Internal Knowledge Agents
RAG-based agents that tap into your documents, handbooks, and databases. Employees ask in plain language, the agent returns accurate answers with citations.
Multi-Agent Systems
Complex tasks split across specialized agents that cooperate. A research agent, a writing agent, a review agent — orchestrated and monitored.
Our process
Use-Case Definition
We clarify what the agent should actually do. Which tasks, which tools, which boundaries. No over-engineering — only what creates value.
Architecture & Tool Design
Choose the LLM (OpenAI, Claude, open-source), design tools and data access. Memory strategy and guardrails are planned from day one.
Implementation
Built in LangGraph, n8n, or direct SDK integration. Logging, evals, and a clean handoff path to humans are part of the default.
Evaluation & Rollout
Agent behavior is measured against real test cases. Gradual rollout, cost and quality monitoring, continuous optimization.
Technologies
Real-World Use Cases
Four AI agents we build today.
An AI agent is not an answer to every question. But for well-defined, recurring tasks, it saves your team hours per week — and makes fewer mistakes than a human on a Monday morning.
Voice Agent for Phone Support
A speaking AI agent takes calls, answers standard questions, and hands qualified leads to your team. 24/7, multilingual, with a clean handoff to humans for complex cases.
Internal Knowledge Agent
Your team asks in plain language — the agent searches handbooks, contracts, project docs, and returns precise answers with citations. No more hunting through five different systems.
Sales Qualification Agent
Inbound leads are qualified automatically: fit questions, budget check, scheduling on your sales team's calendar. Saves the team half a working day per week.
Research & Reporting Agent
Agents that run market, competitor, and customer research on their own. Structured reports instead of hours of browsing — with links and citations for verification.
Frequently Asked Questions
What is an AI agent — and how is it different from a chatbot?
A chatbot answers questions. An AI agent acts — it plans tasks, uses tools (APIs, databases, other systems), makes decisions, and completes multi-step processes. A chatbot tells you when the meeting is. An agent books it, updates your calendar, and sends the invite.
Can we build AI agents without an in-house AI team?
Yes — that's exactly why we exist. We build the agent, integrate it into your systems, and hand it over with documentation. On request we operate it long-term on a retainer — monitoring, model updates, new use cases. You don't need an internal AI team.
Which LLMs do you use?
Depends on use case and data protection needs: GPT-4/5 from OpenAI, Claude from Anthropic, Gemini from Google, or open-source models (Llama, Mistral) on European infrastructure. We pick the model by quality, cost, and compliance — not by hype.
Is an AI agent GDPR-compliant?
Yes, when it's set up properly. We use EU-hosted LLMs, encrypted data connections, and clear data processing agreements. For sensitive data we deploy open-source models on our own infrastructure. GDPR is a default for us, not an add-on.
How long does it take to build an AI agent?
A focused agent with a clear use case (e.g. lead qualification) is live in 2 to 4 weeks. Complex multi-agent systems with deep integrations take 6 to 12 weeks. We always start with a prototype that can be tested immediately.
What does an AI agent cost?
Development starts at €4,500 for a focused use case. Voice agents and multi-agent systems are higher (from €8,000). On top come LLM usage costs (typically €50–400/month) and optionally a retainer for maintenance and expansion.
What can an AI agent NOT do?
AI agents are strong in well-defined, repeatable tasks with clear data sources. They are weak when a task requires real human judgment, empathy, or handling very rare exceptions. That's why we always build in a clean handoff path to humans — the agent knows when to step aside.
What is a voice agent?
A voice agent is an AI agent that communicates by voice — taking calls, answering questions in real time, booking appointments. We use Pipecat, ElevenLabs, and modern LLMs so the voice sounds natural and response latency stays under a second.
Ready to get started?
Let's find out in a free initial consultation how we can implement your project.
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