Implementing AI process automation
How to bring AI into your running business processes: large language models, vision AI and workflow automation as a productive solution rather than a sandbox. We connect GPT, Claude and custom models with your CRM, ERP and DMS. First productive processes in 4 to 8 weeks, GDPR-compliant, on-premise optional.
Why AI gets stuck in mid-sized businesses
Everyone has tried ChatGPT. But integration into real processes is where it stops. That is exactly where a large share of AI initiatives in the DACH mid-market fail.
AI stays an isolated sandbox
Employees use ChatGPT in a browser tab, but the results never land automatically in the CRM, ERP or DMS. Everyone copies manually.
Data protection blocks adoption
Personal data must not go into US cloud AI. Without a secure, GDPR-compliant solution, AI drifts into shadow-IT mode.
Endless pilot phases
Three months of workshops, five-figure consulting fees, and a PDF at the end — but no running process. For many AI projects, the pilot is where it ends.
No system integration
Even good AI models deliver nothing if they are not connected to SAP, DATEV, HubSpot or your line-of-business software. APIs are missing, nobody builds the bridge.
Hallucinations & compliance risk
Without guardrails, validation and an audit trail, you risk wrong data in accounting, contracts or customer communication. That gets expensive in an audit.
Which AI capabilities we embed into processes
Not AI for its own sake, but where it delivers ROI. From document extraction to autonomous agents — embedded in your running systems.
GPT & Claude integration
LLMs such as GPT-4, Claude or local models (Llama, Mistral) wired into your processes via API — with prompt templating, versioning and audit log.
Vision AI for documents & products
Image processing recognises invoices, delivery notes, contracts, product defects or damage photos. Structured data lands automatically in the ERP.
Workflow automation with AI steps
n8n, Make or custom development as the orchestrator — AI is one step in the workflow, not the whole process. Human in the loop where necessary, autonomous where possible.
Custom company AI / RAG bot
A chatbot that knows your contracts, wikis, tickets and product data — RAG architecture, source citations, no hallucinations out of the blue.
AI agents for complex tasks
Agents handle multi-step tasks: lead research, proposal drafts, reporting aggregation. With clear limits and escalation rules.
GDPR-compliant AI operations
EU hosting, on-premise or private-cloud options. Data processing agreements, audit trail, data minimisation — AI deployment ready for the EU AI Act.
The ROI of AI process automation
Typical levers from productive AI projects in the DACH mid-market — no demo slides. We determine the concrete figures for your processes in the AI audit.
How our clients put AI into processes
AI proposal drafts — many hours saved per quote
Problem
Example scenario: the inside sales team of a wholesaler creates complex quotes manually. Each quote takes several hours of research, calculation and drafting — at a high quote volume, quickly a full-time equivalent.
Solution
A custom AI solution accesses the product catalogue, prices, contract history and customer communication. Generates a complete quote draft in minutes; inside sales reviews and refines it.
AI contract analysis — risk check in seconds instead of hours
Problem
Example scenario: for every new client, several existing insurance contracts have to be reviewed manually — scope of cover, gaps, optimisation potential. Each check takes one to two hours, often incomplete under time pressure.
Solution
Vision AI extracts structured data from the PDF contracts. An LLM agent compares against a benchmark database and produces a risk briefing for the broker — including concrete optimisation suggestions.
Custom service bot — ticket volume noticeably reduced
Problem
Example scenario: the service back office answers a high daily ticket volume on spare parts, maintenance intervals and technical specifications — mostly from old manuals, internal wikis and outdated Excel lists.
Solution
A RAG bot knows every manual, spare-parts catalogue and service protocol. Answers a large share of standard enquiries directly with source citation and escalates complex cases to the back office.
Frequently asked questions about AI process automation
Answers to the most important questions about deploying AI productively in business processes.
Classic Robotic Process Automation (RPA) works rule-based: it follows predefined steps and fails as soon as a form or layout changes. AI process automation additionally uses language and vision models to understand unstructured content (emails, PDFs, images, voice messages) and make decisions. They complement each other: RPA for stable click paths, AI for everything that requires understanding — classification, extraction, drafting, summarisation.
Ready to put AI productively into your processes?
In the free AI audit we identify the process with the highest ROI leverage and show how we put it into production in 4–8 weeks.
30 minutes · no obligation · reply within 24 h