Generative KI & Machine Learning

Generative künstliche Intelligenz und Machine Learning sind Treibstoff für unternehmerische Visionen und versprechen positive Folgen für Umsatz, Gewinn und Wettbewerbsposition. Die Herausforderungen: Anwendungsfälle definieren, sowie passende Datengrundlagen und organisatorische Voraussetzungen wie Kompetenzen, Prozesse und Systemintegration schaffen. Klingt komplexer als es ist, denn in den meisten Fällen lohnt es sich, mit einfachen Use Cases und Projekten als Proof-of-Concept zu starten.

Ob leistungsstarke KI-unterstütze Suchen für ein erstklassiges Kundenerlebnis, smarte Personalisierung für mehr Relevanz oder fortschrittliche Analysen für datengestützte Entscheidungen - unsere pragmatischen Lösungen bringen Ihr Business im AI-Game von Null auf Hundert.

Vorteile von generativer KI & Machine Learning:

Kostenreduktion durch Automatisierung
Qualitätsverbesserung von Content
Optimierte User & Employee Experience
Gesteigerte Prozesseffizienz
Erleichterte Entscheidungsfindung
Entlastung des Kundenservice
Höhere Conversion-Raten durch Personalisierung

Was wir tun

AI Semantic Search

Wer sucht, der findet - und zwar ausnahmslos. Durch moderne AI-Modelle erhalten Nutzer:innen relevantere und präzisere Suchergebnisse durch semantische Embeddings und natürliche Sprachverarbeitung (NLP).

Advanced Analytics & Prediction

Über den Tech-Rand hinausdenken: Ableitung tieferer Erkenntnisse aus Daten, um Geschäftsentscheidungen zu verbessern und neue Chancen aufzudecken. Smarte Prognosen und Entscheidungsfindungen u.a. mithilfe von Regression oder Clustering.

AI/ML Readiness

Die Bewertung der Bereitschaft einer Organisation für künstliche Intelligenz und Machine Learning umfasst mehrere Aspekte: die strategische Ausrichtung und unternehmensspezifische Herausforderungen, die Dateninfrastruktur und technologische Reife der Organisation sowie das Fachwissen und die KI-Bereitschaft der Mitarbeiter.

AI/ML Readiness

Let's talk

AI Semantic Search

Search Engine Technology

Semantic Search goes beyond simple keyword matching: It understands the meaning behind queries. By analyzing relationships between words, it delivers more accurate and relevant results. This approach transforms how search engines interact with human language, making searches more intuitive and effective.

The data searching technique uses natural language processing to interpret text meaning and machine learning to analyze patterns. This combination allows for a better understanding of queries, providing more precise results.

Better user experience

Benefit #1

Semantic Search helps users find exactly what they need, and more. It reduces frustration and saves time, leading to happier customers who are more likely to return.

Boosted business performance

Benefit #2

By better matching products to customer queries, Semantic Search increases sales and customer satisfaction. It helps businesses connect more effectively with their audience, leading to higher conversion rates and stronger customer relationships.

Reduced manual work

Benefit #3

Unlike traditional keyword-based search, Semantic Search doesn’t rely on manually managed keyword and synonym lists. NLP, coupled with machine learning, allows the system not only to recognize words but also to grasp the nuances of language, including synonyms, context-specific meanings of sentences and keywords.

Knowledge Management

Retrieval Augmented Generation

Retrieval Augmented Generation (RAG) is a modular technology that combines the capabilities of semantic search and external knowledge bases to act as an extension of existing LLM systems. This is done by integrating additional data from external sources or knowledge databases via the RAG system.

CRAG, or Corrective Retrieval-Augmented Generation, is an advanced technique in AI that enhances the reliability of language models, particularly in tasks requiring accurate information retrieval and generation. It builds upon the traditional Retrieval-Augmented Generation (RAG) framework by incorporating a self-corrective mechanism to ensure the generated text is both relevant and factual.

Less errors, more decisions

Benefit #1

CRAG minimizes the risk of hallucinations (where the model generates incorrect information) by actively verifying the data used for generation. Multi-source validation and contextual analysis ensure decisions are based on accurate, verified information rather than incomplete or outdated data.

Time savings

Benefit #2

Instant access to validated knowledge eliminates hours spent searching through documents, databases, and asking colleagues for information.

Continuous knowledge improvement

Benefit #3

Self-learning loops automatically update and refine the knowledge base, ensuring your organization's intelligence grows smarter over time without manual intervention.

Product Data Intelligence

Research Assistant

Less errors, more decisions

Benefit #1

Time savings

Benefit #2

Instant access to validated knowledge eliminates hours spent searching through documents, databases, and asking colleagues for information.

Continuous knowledge improvement

Benefit #3

Intelligent Sourcing

Process Optimization

Transform your procurement process with AI-powered intelligence that streamlines everything from initial inquiry to final quote. Our smart system dramatically accelerates and simplifies the sales process, supports agents in decision-making, and improves quote quality—strengthening your long-term digital competitiveness.

The platform features AI-powered email parsing, intelligent product matching, automated vendor suggestions, and quote logic. Our central data platform consolidates all relevant information on customers, products, pricing, quotes, and orders as your single system of record. With direct Excel upload, intuitive UI, and guided project workflows, processing becomes rapid and effortless. The modular architecture enables future enhancements like automated quote logic, price analysis, and forecasting.