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AI-Driven Development — Software Development
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01 · Software Engineering

AI-Driven Development

AI in the build process and as a product feature: code assistance, RAG search, ML and LLM capabilities.

Overview

AI is not just a buzzword for us — it is an integral part of how we work: In development, we use AI-powered code assistance, automated test generation, and intelligent code review.

As a product feature, we build natural-language query interfaces (RAG), intelligent document analysis, predictive models, and LLM-powered automations.

We deliberately choose between classical ML, pre-trained models, and custom LLM solutions — always driven by the specific task and available data.

Typical use cases

  • Natural-language Q&A platforms over enterprise data (RAG)
  • Intelligent document analysis and classification
  • Generative-AI platforms for brand-compliant content creation
  • Predictive models for forecasting, churn, and anomaly detection
  • AI-powered quality assurance and automated testing

Technologies

Backend & integration
Java / J2EE Spring Quarkus GraalVM .NET / C# Node.js Python PL/SQL
Frontend
React Angular Vue.js TypeScript
Mobile
Swift / SwiftUI Kotlin React Native Expo Capacitor / Vue.js Flutter
BPM & workflow
Red Hat PAM / jBPM IBM Business Automation Manager Open Editions Camunda
Databases
PostgreSQL MS SQL Oracle MySQL MariaDB MongoDB Elasticsearch Redis
Messaging & middleware
Apache Kafka RabbitMQ Hazelcast Memcached
CI/CD & DevOps
Docker Jenkins GitHub Actions GitLab CI ArgoCD SonarQube

Related case studies

More focus areas

Let’s talk about your initiative.

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