From single-purpose chatbots to autonomous agent workflows

The AI services market is full of consultancies that hand you a research report and walk away. We build working systems your team uses every day, then keep optimizing them.

Knowledge-Grounded Chatbots

Customer support, internal helpdesk, sales qualification. Grounded in your documentation via RAG so they don’t hallucinate. Escalation rules built in — they hand off to humans when uncertain.

Agentic RAG Over Your Knowledge Base

Production-grade retrieval over your wiki, docs, tickets, contracts. Multi-step reasoning with tool use. Source citations on every answer so users can verify.

Custom AI Agents

Sales follow-up agents, ops triage agents, support deflection agents, research agents. Built around the specific workflow you need automated, with audit trails and approval gates where they matter.

Fine-Tuning & Prompt Engineering

When base models don’t cut it: domain-specific fine-tuning on your data, evaluation harnesses, prompt-versioning infrastructure so changes are testable and reversible.

POC to Production Pipeline

Getting from prototype to production is where most AI projects stall. We take working prototypes through evaluation, observability, cost control, and rollout — every engagement ends with a production deployment, with monitoring and cost controls in place from day one.

Agent Orchestration Layer

Multi-agent systems where specialist agents (research, drafting, review, dispatch) coordinate via a control loop. Each one auditable. The whole thing observable.

From “AI sounds good” to “running in production”

Use-Case Discovery

Paid 1-hour scoping call (credited back if you sign) where we identify one specific workflow worth automating. We map the inputs, the decisions, the outputs, and what success looks like. Written summary at the end with concrete findings.

4-Week Pilot

Fixed-price pilot: working agent in your environment in 4 weeks. Real data, real users, real evaluation. You decide whether to take it to production based on measured results from your environment.

Production & Continuous Improvement

Production deployment with observability, cost guardrails, and an evaluation harness. Then weekly: prompt tuning, retrieval improvements, edge-case handling. The agent improves every week throughout the engagement.

What you won’t get from us

A €100k strategy deck. The big-name consultancies are great at frameworks and slow to ship. Our pilots are fixed-price builds that land in production. The whole engagement costs less than one quarter of their typical retainer.

A “platform” you can’t leave. We use standard frameworks (LangChain, LlamaIndex, Vercel AI SDK — or your choice), check everything into your repo, and document the architecture. You own the code, the prompts, and the evaluation criteria. The “POC then abandon” pattern is the industry default. 64% of AI pilots never make it to production for exactly this reason. We work the inverse way: the pilot already assumes production, and our retainer is built around continuous improvement once it’s live.

Frequently asked questions

What is an AI agent?

An AI agent is software that uses a large language model (LLM) to reason, make decisions, and take actions autonomously within a defined workflow. Unlike a chatbot that just responds to prompts, an agent can use tools (search, write files, call APIs, query databases), break a goal into sub-tasks, and execute them in sequence — with or without human checkpoints. Examples: a support triage agent that reads incoming tickets, categorizes them, drafts responses, and escalates edge cases; or a research agent that gathers market data, synthesizes findings, and produces a briefing document.

How much does AI automation cost?

A discovery scoping call is €200 (credited back on engagement). Fixed-price pilots typically run €5,000–€15,000 for a focused single-agent build. A full multi-agent system or RAG deployment over a large knowledge base is typically €20,000–€60,000. Ongoing improvement retainers start from €5,000 / month.

How long does it take to implement AI agents?

A focused pilot is 4 weeks. That’s a working agent in your environment, on your data, evaluated by your team. Production hardening and rollout adds another 2–4 weeks. Multi-agent systems take longer — 8–16 weeks depending on workflow complexity. We size it before we start.

What business processes can be automated with AI agents?

The best candidates are processes that are currently handled by humans reading documents, making repeatable decisions, and routing or responding. Examples: customer support triage and response drafting; internal Q&A over policy docs, contracts, or technical manuals; sales lead research and personalized outreach drafting; invoice and document data extraction; compliance monitoring against policy text. If a human reads it, decides, and writes — an agent can likely do it.

What’s the difference between an AI automation agency and an AI consulting firm?

A consulting firm tells you what to do; an automation agency builds it. Consulting typically ends with a strategy document or vendor recommendation. We end with a running system in your environment. We do offer scoping and strategy — always as the first step toward a working build.

Do I need to have my data organized before starting?

You do not need to. Part of our discovery process is assessing what data exists, in what form, and what preparation is needed for retrieval. Messy wikis, PDF-heavy knowledge bases, and poorly structured ticket systems are the common starting point. We scope the data preparation work as part of the engagement so it’s budgeted from the start.

Tell us about the workflow you want automated

One specific use case. We’ll come back with whether it’s viable, what the pilot looks like, and what it costs — straightforward answers in writing.

Contact us → See pricing

AI Automation Agency