// AI implementation
AI Implementation.
From Idea to Production System.
Introducing AI in a company takes a suitable use case, a solid architecture and a clean connection to the systems you already run. For mid-sized companies and enterprises, one team handles both consulting and delivery and supports you from strategy to go-live.
// The starting point
Many AI Projects
Never Reach Production.
is the starting price for an AI workshop with us
weeks to a first working prototype with us
AI systems we have taken into production so far
industries in which our AI systems are in use
Technology Before Use Case
Many projects start with "We need AI" and no clear idea of what for. Even an expensive tool achieves little without a sound business case behind it.
Data Quality Ignored
An AI solution is only as good as the data it works with. That is why we review your data and its quality before choosing a model.
Started Too Big
Starting with a large enterprise platform often means a long wait for the first result. One agent working in daily operations is worth more than a 12-month project that never goes live.
Teams Not Involved
Without change management, new technology goes unused. AI only pays off when your employees understand it and use it in their daily work. Our AI training helps with exactly that.
// Use Cases
AI Use Cases
in Business.
Customer Service
AI agents for ticket automation, intelligent routing and round-the-clock first-level support, connected to Zendesk, Freshdesk or Intercom.
Marketing & Content
AI-powered content creation, AI SEO, campaign management and social media automation. More on this under Agentic Marketing.
Sales & CRM
Lead scoring, CRM automation, follow-up sequences and meeting scheduling. The AI qualifies and prioritizes leads, and your sales team closes the deals.
Operations & Processes
Process automation with n8n for data capture, document processing, monitoring and reporting. If you prefer, everything runs on your own servers.
Knowledge Management
Internal knowledge bases with RAG make manuals, policies and documentation searchable, so employees find the right answer quickly.
Finance & Controlling
Automated invoice processing, anomaly detection, forecasting and spend analysis. AI finds patterns in large data sets that are easy to miss in manual reviews.
// Our approach
5 Steps to
Production AI.
AI Readiness Assessment
Together with you, we establish where your company stands today, which processes can be automated and what data is available. The result is a list of the use cases with the highest expected ROI. Learn more about our AI consulting.
Use Case Prioritization & Roadmap
We prioritize the use cases by impact and feasibility and turn them into an AI strategy with first steps you can implement quickly and long-term goals.
Proof of Concept
Within 2-4 weeks you get a working prototype that runs on your real data and processes. You see early on whether the solution holds up, before you invest in full implementation.
Production Implementation
The PoC becomes a production system: we integrate the AI into your existing IT and take care of API connections, security, monitoring and logging. Deployment runs on your infrastructure or on EU servers with Docker, compliant with GDPR and the EU AI Act.
Training, Scaling & Optimization
Team training, monitoring and ongoing optimization. We then connect further use cases and departments so the solution grows with your company. If you wish, we take over operation from EUR 2,500 per month.
// Prerequisites
Is Your Company
Ready for AI?
Good Prerequisites
Where We Support You
// FAQ
Frequently Asked
Questions About AI Implementation.
What does AI implementation mean?
AI implementation is the process of integrating artificial intelligence into existing business processes and IT systems: from use case identification through data preparation and model selection to system integration, testing, and deployment.
How do you introduce AI in a company?
In five steps: AI Readiness Assessment, use case prioritization, Proof of Concept with real data, production implementation, and scaling. We guide the entire process, from strategy to go-live.
What are typical AI use cases?
Customer service (chatbots, ticket automation), marketing (content, campaigns), sales (lead scoring, CRM), operations (process automation), HR (recruiting), finance (invoices, forecasting), and knowledge management (RAG databases).
How long does an AI implementation take?
A Proof of Concept takes 2-4 weeks, a single AI solution 6-12 weeks until it runs in production. We plan company-wide programs over 3-12 months. You often see first results after 1-2 weeks.
What does an AI implementation cost?
Setup & Discovery starts at EUR 5,000, delivery runs in sprints of 2-4 weeks at EUR 8,000 each. A single solution typically costs EUR 15,000-40,000, company-wide programs start at EUR 50,000. Optionally, we run the system for you from EUR 2,500/month; tokens and hosting typically add EUR 500-2,000/month. Details under Approach & Pricing (in German).
What mistakes should you avoid when implementing AI?
Typical mistakes are putting technology before the use case, underestimating data quality, starting too big, leaving employees behind and overlooking GDPR or the EU AI Act. Our AI consulting helps you avoid these mistakes.
// Next step
Ready for
AI in Practice?
In a free 30-minute initial call, we work out which use case offers your company the most value and outline the path to an AI system in production.
Book an Initial Call