AI Process Automation
Replace manual routine work with intelligent automation. Not someday — in 4 weeks. Not in theory — with measurable results.
of companies will use AI automation by 2026 (Gartner)
time savings on automated processes
fewer errors with AI-powered processing
to ROI on typical automation projects
Sources: Gartner 2025, Bitkom 2025, Synclaro Benchmark 2025
The Problem: 82% Manual Workflows
Most mid-sized companies still run processes designed a decade ago.
Your team copies data from emails into the ERP. Invoices are typed in by hand. Customer inquiries pass through three inboxes before anyone responds. Purchase orders are derived from inventory levels tracked in spreadsheets.
It works — but it costs: 30–40% of your skilled employees' time goes into routine tasks that AI could handle in seconds.
AI process automation changes that. Not through an expensive big-bang solution, but process by process — starting where the leverage is greatest.
6 Processes AI Improves Immediately
Concrete before-and-after comparisons from real businesses.
Invoice & Document Processing
80% time savingsBefore — manual
Employees manually type invoice data into the ERP. 10 minutes per invoice, typos included.
After — with AI
AI reads invoices automatically (OCR + classification), validates data, and posts to ERP. 2 minutes per invoice.
Customer Service & Ticketing
60–80% auto-resolvedBefore — manual
Every customer inquiry is manually read, categorized, and routed to the right department. Response time: hours.
After — with AI
AI categorizes inquiries automatically, routes tickets, and answers standard questions instantly via chatbot.
Quote & Order Management
75% faster quotingBefore — manual
Quotes are manually assembled from templates. Pricing pulled from multiple spreadsheets. Lead time: 2 days.
After — with AI
AI generates quotes from CRM data, calculates pricing automatically, and sends after approval.
Human Resources & Recruiting
70% less screening effortBefore — manual
HR manually screens 200 applications, matches requirements, and coordinates interviews via email.
After — with AI
AI filters applications by qualification profile, suggests top candidates, and schedules interviews automatically.
Procurement & Supplier Management
15–25% procurement cost reductionBefore — manual
Purchase orders derived manually from inventory levels. Supplier evaluation based on gut feeling.
After — with AI
AI analyzes consumption patterns, forecasts demand, and creates optimized purchase orders with supplier comparison.
Quality Control & Production
95%+ detection rateBefore — manual
Visual inspection by employees — subjective, fatigue-prone, and not scalable.
After — with AI
Computer vision detects defects in real time, documents automatically, and triggers alerts on deviations.
RPA vs. AI Automation
Two technologies that are strongest together.
| Capability | RPA | AI |
|---|---|---|
| Rule-based | ||
| Learns from data | ||
| Structured data | ||
| Unstructured data (text, images) | ||
| Decision-making | ||
| Language understanding (NLP) | ||
| Simple setup | ||
| Combination (hyperautomation) |
Our approach: Hyperautomation. We combine RPA for structured tasks with AI for intelligent decisions. The result: end-to-end automated process chains from start to finish.
How We Automate Your Processes
Four phases — from initial consultation to scaled automation.
Process Analysis
Which processes consume the most time? Where do errors occur? We identify the top automation candidates and assess ROI potential.
Pilot Project
We automate the highest-impact process in 4–8 weeks. Not a massive project, but a focused proof that it works — with your real data.
Integration
Connection to your existing systems (ERP, CRM, DMS). The automation runs seamlessly in the background while your employees continue working as usual.
Scale
Roll out successful automations to additional processes. Train your team. Set up monitoring. Continuously optimize.
Technologies We Use
Proven tools — no experiments with your business processes.
AI & Machine Learning
- OpenAI / Claude API
- LangChain
- Azure AI Services
- Custom ML Models
- Computer Vision
Automation
- n8n / Make
- Python
- Node.js
- Cloudflare Workers
- Docker
Integration
- REST / GraphQL APIs
- SAP, DATEV, MS Dynamics
- Salesforce, HubSpot
- Legacy Systems
- Real-time Synchronization
What Can Automation Save Your Business?
Calculate your concrete savings potential — in 2 minutes, free of charge.
Frequently Asked Questions About AI Process Automation
Everything you need to know about intelligent automation.
What is AI process automation?
AI process automation combines artificial intelligence with workflow automation. Unlike traditional automation (RPA), which operates purely on rules, AI can also process unstructured data, learn from mistakes, and make decisions. This makes not only simple but also complex business processes automatable.
What is the difference between RPA and AI automation?
RPA (Robotic Process Automation) executes rule-based tasks — like a macro for business processes. AI automation goes further: it understands text, recognizes patterns, makes decisions, and keeps learning. The best solution is often a combination of both approaches — called hyperautomation.
Which processes are suitable for AI automation?
Repetitive processes with high data volumes are especially suitable: invoice processing, document classification, customer service inquiries, quote generation, HR screening, and quality control. Rule of thumb: if a process is frequent, error-prone, and involves data, it's a candidate.
What does AI process automation cost for SMEs?
Simple automations start at EUR 5,000. Typical pilot projects with AI integration range between EUR 10,000 and 30,000. ROI is achieved on most projects within 2–12 weeks. A free initial consultation helps assess the potential realistically.
Do I need my own IT department for this?
No. Thanks to no-code/low-code platforms and turnkey AI solutions, getting started is possible even without a large IT team. We implement the solution, train your team, and offer managed services for ongoing operations if desired.
How long does implementation take?
A pilot project typically takes 4–8 weeks. Simple workflow automations can go live in 1–2 weeks. Full automation of multiple processes with system integration takes 2–4 months.
Is AI automation GDPR-compliant?
Yes — when implemented correctly. We use GDPR-compliant solutions with data processing in European data centers. Personal data is encrypted, access rights are granularly controlled, and processing logs are automatically documented.
What happens when the AI makes mistakes?
Every AI automation follows a human-in-the-loop approach: when decisions are uncertain, an employee is brought in. Over time, the system learns and the error rate decreases. AI error rates are typically far below human error rates on routine tasks.
Can existing systems (ERP, CRM) be integrated?
Yes. System integration is our core specialty. We seamlessly connect AI automations with SAP, Microsoft Dynamics, DATEV, Salesforce, HubSpot, and many other systems — including legacy software without modern APIs through custom interfaces.
What is hyperautomation?
Hyperautomation combines RPA, AI, machine learning, and Intelligent Document Processing (IDP) into end-to-end automated process chains. Instead of individual tasks, entire workflows are automated from start to finish. According to Gartner, by 2026 over 80% of companies will use at least one form of hyperautomation.
Which process costs you the most time?
30-minute initial consultation — free. We identify your top 3 automation candidates and show the concrete ROI.