soneo

AI Engineering

Customized AI solutions for your business

Our AI Engineering Approach

At soneo, we know that every challenge is unique. That's why we offer customized AI solutions, tailored to your company and industry.

Our technologies are based on current expertise and a deep understanding of your processes. Together, we identify potential for AI application in your business and develop a precisely tailored concept.

Development takes place entirely in-house, allowing us to respond flexibly and quickly to your requirements, for a solution that fits you exactly.

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Technologies and Methods

From RAG systems to AI agents and process automation. We build on production-proven frameworks like LangChain and LangGraph, trusted by leading enterprises and SMEs across the DACH region.

01

RAG Systems & Knowledge Management

Retrieval-Augmented Generation (RAG) connects your internal knowledge base (standards, guidelines, project documentation) with Large Language Models. Built on LangChain, we develop searchable AI systems that deliver precise answers with source references to your employees. Ideal for mechanical engineering and technical documentation in SMEs.

02

LLM Integration and AI Integration for Enterprises, GDPR-Compliant

We integrate modern language models and AI solutions into your existing business processes – securely, scalably, and GDPR-compliant. From API integration to EU hosting and self-hosting, we develop the right architecture for your use case and ensure full control over your company data.

03

AI Process Automation

Built on n8n and LangChain, we automate repetitive workflows end-to-end: document processing, email triage, report generation, and more. Our AI automations go beyond traditional rule-based systems: they understand context, learn from data, and scale with your business.

04

Multimodal AI Applications

Our AI systems process not just text, but also technical drawings, PDFs, images, and spreadsheets. Through multimodal models, we unlock information from diverse data sources, especially relevant for engineering, manufacturing, and technical documentation in DACH industries.

05

AI Agents & Agentic AI

Using LangGraph, we build autonomous AI agents that independently execute multi-step tasks: from research and data analysis to automated decision preparation. Our agent systems are production-ready, monitorable, and integrable into existing business processes, providing a growing competitive advantage for SMEs across the DACH region.

06

AI Strategy & Implementation

Before technology comes strategy: together we identify the AI use cases with the highest ROI, develop an actionable roadmap, and guide you from proof of concept to production deployment. Proven across 10+ AI projects in the DACH region, with a typical project timeline of 8 weeks.

Typical Use Cases

01

Knowledge Management

AI-powered search across internal documentation, standards, and guidelines. Engineers find answers in seconds instead of hours.

02

Document Automation

Automatic extraction, classification, and summarization of documents, from invoices and technical specifications to contracts.

03

Intelligent Assistants

Company-specific chatbots for support, HR, or sales, trained on your knowledge and integrated into existing systems.

Measurable Results

In our projects to date, we have achieved tangible results: 3 to 6 hours of time savings per engineer per week, over 95% accuracy on document-based queries, and an average project timeline of 8 weeks to productive deployment.

Automation Process

Parts of a process or entire workflows are represented in automation and performed by a machine or AI. This enables rapid processing of large amounts of data in a short time with high quality.

01

Analysis of Routine Tasks

Together we analyze the potential routine activities that can be performed automatically by the machine or artificial intelligence.

02

Setting Up a Test

A Proof of Concept (PoC) is essential when automating individual processes to ensure that the automation works flawlessly before it can be fully implemented.

03

Implementation of Automation

After successfully completing the test phase, we implement the automation for your company in the defined process.

04

Regular Maintenance and Improvement

We ensure the ongoing functionality of the automation through regular maintenance.

Related Services

01
Service

Data Management

Successful AI projects require a solid data foundation. Learn more about our Data Management services.

02
Service

Workshops

Our AI workshops equip your team with the knowledge to effectively leverage AI solutions in daily operations.

Ready for the next step?

Discover how our AI solutions can transform your company. Contact us for a non-binding consultation.

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Frequently Asked Questions

About AI Engineering: approach, data, security, timelines, and integration

AI Engineering is the development and implementation of tailored AI solutions to automate, optimize, or innovate business processes. soneo.ai supports you end to end, from analysis and concept to integration and operations.

Common projects include process automation, AI assistants, internal knowledge systems, document/text processing, and generative AI features. The key is always clear business value, a strong data foundation, and clean integration.

Typical steps are: needs & goal definition, data analysis/preparation, model selection & prototype, integration into systems, then monitoring and ongoing optimization. The focus is on a fast, validated MVP instead of long theory phases.

An MVP can often be delivered in 2 to 6 weeks; more complex integration projects tend to take 2 to 4 months. The timeline mainly depends on data readiness, integration effort, and security/compliance requirements.

Depending on the use case: structured data, text data, documents, processes, or feedback data. If data is missing or unstructured, Data Management is often the best first step.

GDPR compliance and secure infrastructure are standard requirements; depending on needs, cloud setups (including EU options) or on‑prem are possible. We also focus on access concepts and traceable results when the process requires it.

The goal is that AI works where teams already work. We integrate via interfaces and into your system landscape. We ensure stable processes, clean monitoring, and maintainability so the solution doesn’t “break” in day-to-day use.