Service
AI Assistants & LLM Solutions
RAG applications, conversational assistants, and copilots based on modern LLM stacks.
What to expect
We develop LLM-based applications that resonate in your users' daily lives — from Retrieval-Augmented-Generation to conversational assistants and domain-specific copilots. Always with a focus on quality, cost, and productive scaling.
- RAG Architectures on Proprietary Knowledge Bases
- Conversational Assistants and Voice Interfaces
- Prompt, Model, and Evaluation Engineering
- Operation and Cost Monitoring of LLM Workloads
Selected technologies
OpenAI
Anthropic
LangChain
Hugging FaceSelected reference projects
All projectsReal Estate Industry
Scaling a Conversational AI Assistant
A conversational AI assistant was developed from an early product stage towards a production-ready, widely deployable solution. The work included the integration of additional use cases, improving model performance, and scaling deployment and operations. Particular attention was paid to coordination with product and development teams, solving scalability issues, and continuous adaptation to real user requirements.
Learn moreIT and Digital Services
AI-Powered Reporting and Chat Application
For an IT service provider, a modern web application was developed as an AI-powered chat and reporting entry point. The solution can connect various systems and data sources, convert inquiries into structured queries, and generate and distribute reports. The architecture was deliberately designed for extensibility, allowing additional functions, data sources, and business use cases to be integrated incrementally.
Learn moreReal Estate Industry
Centralized AI Services for Digital Real Estate Offerings
Existing AI-driven services for a digital real estate platform were expanded and integrated into a scalable, central service landscape. The scope of services included the further development of models for user intent and marketing evaluation, as well as services for automated text and speech processing. In addition to technical integration, the focus was on optimizing model deployment, operations, and maintenance, as well as reliable collaboration with interdisciplinary product teams.
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AI-Driven Process Automation in Real Estate Management
Business processes for a real estate company were analyzed and further developed using a low-code and AI-supported automation platform. The solution connects workflows, apps, and evaluations with external systems and APIs. In addition to implementation, the focus was on identifying suitable automation potential, governance and security standards, monitoring, and empowering specialist departments.
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