Autonomous AI agents that handle onboarding processes. RAG pipelines that make your company knowledge searchable. Workflow automation that relieves entire departments. In production use - including in the medical sector.
What is an AI agent?
An AI agent is a software system that uses a language model to independently plan and execute multi-step tasks - such as checking data, querying systems, drafting e-mails and triggering follow-up actions. Unlike a chatbot, an agent does not just answer - it works.
Substance instead of slogans
Autonomous AI agents
Agents that take over complete process chains: checking documents, extracting data, updating systems, asking follow-up questions. Proven in production in onboarding processes in the medical sector.
RAG pipelines & knowledge bases
Retrieval-augmented generation makes internal documents, contracts and manuals searchable in natural language - with source citations and without hallucinations.
Document automation
Automatically classify, extract and transfer invoices, forms and contracts into your systems - including validation rules and four-eyes workflows.
Workflow automation
From e-mail triage to automatic quote generation: processes are analysed, automated and equipped with monitoring - with n8n, custom services or both.
GDPR-compliant architecture
EU hosting, data minimisation, data processing agreements and - where necessary - local models. AI deployment that also stands up to the data protection authority.
Measurable ROI
Every automation is instrumented with metrics: hours saved, throughput times, error rates. AI as an investment with evidence, not an experiment.
Typical projects
- AI agents for business processes
- RAG systems & internal knowledge search
- Document extraction & classification
- Workflow automation (n8n, custom)
- AI chatbots with company knowledge
- AI strategy & feasibility analysis
Technology stack
Proven standards instead of exotics: every technology in use has a large ecosystem and long-term maintainability - so your project can still be extended in five years.
Projects from this area
KI-AutomatisierungMedizinischer Sektor
AI Agents & Workflow Automation
Autonome KI-Agenten übernehmen Onboarding-Prozesse im medizinischen Sektor: Dokumentenprüfung, Datenextraktion und Systempflege - mit LangChain, RAG und Pinecone.
Finanz-AutomatisierungDevpack
Offene-Posten-Automatisierung
Automatisierte Verarbeitung offener Posten: Zahlungsabgleich, Mahnläufe und Buchhaltungs-Sync ohne manuelle Zwischenschritte.
Frequently asked questions about ai & automation
How much does AI automation cost for companies?
Focused automations (e.g. document extraction) start at around €5,000, complex AI agent systems at €15,000. A feasibility analysis (from €1,500) clarifies upfront which process offers the best cost-benefit ratio.
What is the difference between a chatbot and an AI agent?
A chatbot answers questions in a dialogue. An AI agent executes tasks independently: it plans work steps, calls systems and databases, makes rule-based decisions and triggers follow-up actions. Agents replace process work, chatbots replace search fields.
Is using AI possible in a GDPR-compliant way?
Yes, with the right architecture: EU hosting or local models, data minimisation, pseudonymisation and data processing agreements with all providers. The data protection assessment is a fixed part of every AI project by Astra IT Solutions.
Which processes are suitable for AI automation?
Processes with high volume, clear rules and a document or text focus work best: inbox handling, onboarding, invoice verification, support triage, report generation. Rule of thumb: what a trained employee completes in under 10 minutes following a pattern, an agent can usually take over.
How quickly is an AI project productive?
A first productive prototype typically stands after 3 to 5 weeks. It is then extended iteratively: more process steps, more data sources, more autonomy - each with measurement of result quality.
Guides & matching tools
KI-Agenten im Unternehmen: Was sie können und wo sie sich rechnen
KI-Agenten führen eigenständig mehrstufige Geschäftsprozesse aus - vom Dokumenten-Check bis zur Systempflege. Ein Praxisleitfaden mit echten Einsatzszenarien und ROI-Rechnung.
RAG einfach erklärt: So macht Retrieval-Augmented Generation Firmenwissen nutzbar
RAG (Retrieval-Augmented Generation) verbindet Sprachmodelle mit Ihren eigenen Dokumenten - für präzise, quellenbasierte Antworten ohne Halluzinationen. So funktioniert die Technik.
Chatbot vs. KI-Agent: Der Unterschied, der über Ihren ROI entscheidet
Chatbots beantworten Fragen, KI-Agenten erledigen Arbeit. Warum diese Unterscheidung über Erfolg oder Frust von KI-Projekten entscheidet - mit Entscheidungsmatrix für Unternehmen.
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