Conversational AI Experts in Munich
in minutes from over 15,000 CVs with the power of AI.Hire experts who design chatbots, virtual assistants, and voice bots, connect NLP and NLU workflows, and tune dialogue flows for clear handoffs and reliable support. FRATCH matches you fast and precisely with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Conversational AI
Philipp T.
Last position:
Founder & CEO at FRATCH.IO
AI-native B2B SaaS for freelancer sourcing; DACH market.*
Enterprise partnerships across four industries: structured and closed multi-stakeholder deals with Telefónica (Telco), Emma Matratzen (Retail), Nürnberger Versicherungen and Flatex (Financial Services), Hubert Burda Media and Serviceplan Gruppe (Media).
Revenue and growth: scaled FRATCH from €0 to €3.8M annual GMV, with ~80% of revenue sourced from founder-led direct outreach and partner relationships.
Channel partnerships: sold FRATCH as a SaaS solution to recruiting firms (e.g., YER) — built the partner-enabled motion alongside direct enterprise sales.
Team build: scaled FRATCH from solo founder to a team of 7 across engineering, product design, operations, and supply outreach.
Proprietary network asset: onboarded 15,000+ freelancers as registered users — the proprietary DACH network powering FRATCH's matching.
Built and launched FRATCH GPT (fratch.io/gpt): a production conversational AI agent. Architected the full stack — LLM orchestration, embeddings, re-ranking — with hands-on involvement in technical design and execution.
GTM build: owned the full go-to-market stack — outbound, LinkedIn (organic + paid), content, and sales enablement.
Hans-Heinrich W.
Last position:
Senior AI Product Engineer | Flutter · MVP · Agentic Engineering at struppilog.com
struppilog.com – Digital health record for pets / MVP → Full Product
Design, development, and full further development of a digital health platform for pets – from my own MVP development to a fully built and production-ready platform.
Independent concept and development of the MVP Development of the full application with Flutter/Dart and Firebase Expansion of the MVP into a full digital health record with health data, findings, allergies, medications, documents, and emergency data Development of user registration, authentication, roles, data models, and secure user interactions Implementation of QR-code-based data exchange and digital interaction features Development of a multilingual, responsive web application Integration of AI-supported features and AI/agentic workflows Development and continuous improvement of product logic, UX/UI, and technical architecture Building and expanding a scalable cloud-based solution with Firebase Integration and further development of APIs and external services Use of AI-native / agentic engineering to speed up development, testing, debugging, and product iteration Independent implementation of all other features and technical extensions Continuous further development of the MVP into a full digital product
Impact: The MVP I built myself was continuously developed technically and functionally into a broad, production-ready platform – including frontend, backend, data model, authentication, UX/UI, APIs, cloud infrastructure, and ongoing product development.
Hans-Christian R.
Last position:
AI Voice Systems Consultant at QuantaLingo
Consulting and prototype work on AI voice and multilingual agent systems, using AI-assisted delivery across realtime translation prototypes, call-centre automation, and voice-to-voice consultation workflows.
- Built and advised on AI voice / agentic conversation prototypes, including realtime translation and consumer-facing consultation experiences.
- Worked across call-centre automation, voice UX, product architecture, implementation tradeoffs, and prototype development.
Nurbüke T.
Last position:
Working Student – Software Engineer at Rohde & Schwarz
- Developing software tools within the EICACS program (LDACS project) supporting secure avionics communication.
- Built Python-based automation and monitoring services to validate AI components under Trustable AI guidelines.
- Designed CI/CD and test pipelines improving reproducibility and reliability across teams.
Will C.
Last position:
Freelance Writer | UX Content Designer | AI Content Engineer at Cade Communications
- Airbus: Forum - feature writing on technology for internal employee magazines
- Bosch: Security and Safety Systems - feature writing and copy writing for industry magazines and social media
- Dassault Systemes: 3DExcite - screenwriting for corporate vision videos on digital transformation
- Deutsche Telekom: Brand & Design - copywriting and translating guidelines and books on design thinking
- GoTo: LogMeIn Rescue & GoTo Admin - UX writing and AI prompt engineering for IT support software
- MTU Aero Engines: Aeroreport - judging and ranking the editorial quality of B2B and B2C translations
- Siemens: Financial Services - copywriting and editing for internal finance sites and newsletters
- Zeiss: Beyond Design System - UX writing for voice & tone guidelines to help improve conversational AI
Mohamed S.
Last position:
Machine Learning Engineer (Part Time) at E.ON Digital Technology
- Designed and implemented an advanced, agentic RAG pipeline using LangChain and LangGraph for structured data extraction from PDFs, utilizing tools, state management, and OpenAI LLMs (GPT-4) to improve accuracy and handle complex document structures.
- Developed a Google AI agent for extraction of structured information from PDF documents and deployed the agent on Vertex AI.
- Architected data pipelines using Azure Data Factory and Databricks to ingest data from Azure Blob Storage, process it with PySpark, and load it into Azure SQL Database via Linked Services.
- Containerized AI agents and services using Docker for consistent local development and deployment.
- Utilized PySpark and Dask for database querying in coordination with Azure Blob Storage and Document Storage.
- Created a ReAct agent that extracts structured data from PDF documents using tools and integrating Azure Document Intelligence.
- Contributed to the CPO invoices validation check project using Databricks to find existing CDRs and calculate total valid costs.
- Developed a conversational AI agent (chatbot) with a FastAPI backend, integrating RAG for precise tariff extraction and deployed the service using Azure Container Apps.
- Tools used: Azure, Azure OpenAI, Azure Document Intelligence, Azure Blob Storage, Google ADK, Google Cloud, Vertex AI, Gemini, Databricks, LangChain, LlamaIndex Ollama, Docker, PySpark, Azure SQL, Azure Data Factory, Azure AI Agent, Microsoft SQL Server
Discover over 15,000 top freelancers
Statistics of experts using Conversational AI
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
3.5 years
Positions per freelancer
6
Top business areas
Product Development, Information Technology, Business Intelligence
Top industries
Information Technology, Media and Entertainment, Healthcare
Bachelor's degree or higher
80%
Master's degree or higher
60%
Certifications per freelancer
0
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 16 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Munich using Conversational AI
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 16 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Conversational AI experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (100%)
- Media and Entertainment (67%)
- Healthcare (50%)
- Manufacturing (50%)
- Professional Services (50%)
- Aerospace and Defense (33%)
- Education (33%)
- Transportation (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What it covers
Conversational AI is used to build systems that understand intent, answer questions, and guide users through tasks in chat or voice. It shows up in customer support bots, self-service assistants, internal help desks, and voice interfaces. The goal is simple: fast, useful conversations that reduce manual work.
Core building blocks
- Intent detection and entity extraction
- Dialogue flow design and fallback handling
- NLP, NLU, and response generation
- Integrations with CRM, ticketing, and knowledge bases
- Testing for accuracy, tone, and edge cases
Strong specialists know how these parts fit together and how to keep the conversation useful when users go off script.
Tooling and stacks
Teams often work with Dialogflow, Microsoft Copilot Studio, Amazon Lex, Rasa, and OpenAI-based components. They also need analytics, logging, prompt design, and secure API integration. A good expert can choose the right stack for web chat, messaging apps, or voice channels.
When companies bring in help
Companies hire freelance expertise when a bot needs a redesign, a new channel, better routing, or cleaner content. This is common in Munich for firms that serve customers in German and English, or that need careful alignment with support, sales, and product teams. Freelancers help when internal teams need focused delivery without long staffing cycles.
What strong specialists deliver
- Clear conversation maps and user journeys
- Working prototypes and production-ready assistants
- Prompt, intent, and fallback tuning
- Documentation for handover and ongoing care
- Practical advice on privacy, quality, and maintenance
The best professionals write for real users, not for demos. They keep answers short, handle edge cases well, and make the system easier to improve over time.
What to look for
Look for experience with real deployments, not just proof-of-concepts. A strong Conversational AI specialist can explain why a flow fails, how to fix recognition issues, and how to connect the assistant to business systems. They should also be able to work with product, support, and content teams.
Frequently asked questions
What clients ask us most about Conversational AI — answered in short.
Conversational AI is used to build chatbots, voice bots, and virtual assistants that answer questions, route requests, and complete simple tasks. In practice, it supports customer service, internal support, lead qualification, booking flows, and knowledge access. The best systems feel natural and still stay tied to business rules.
Not exactly. A chatbot is often the visible interface, while Conversational AI is the mix of intent detection, dialogue logic, language handling, and integrations behind it. Many teams start with a chatbot and then add better understanding, fallback paths, and data connections.
A strong Conversational AI specialist usually also knows NLP, conversation design, API integration, and content design for short, clear responses. Depending on the project, experience with CRM systems, ticketing tools, speech interfaces, and analytics is also valuable. Security and privacy awareness matter when the assistant handles user data.
That depends on control, hosting, and how much customization you need. Conversational AI projects on Dialogflow often favor quick setup, Rasa suits teams that want more control, and Copilot Studio fits Microsoft-centered environments. A good freelancer can compare them against your channels, data sources, and maintenance needs.
Simple FAQ bots need less effort than assistants that handle authentication, routing, or multi-step workflows. For Conversational AI, the real need is someone who has shipped something similar to your use case, not just someone who has read about the tools. If the bot touches business-critical flows, proven delivery matters more than tool familiarity alone.
Yes, most Conversational AI work can be done remotely because the main tasks are design, integration, testing, and iteration. On-site time can still help when teams need workshops, stakeholder alignment, or direct access to sensitive internal knowledge. For Munich companies, a hybrid setup is often the practical middle ground.
Look for clarity in the conversation design, solid fallback behavior, and answers that stay on task. A good Conversational AI specialist measures how the assistant handles real user questions, not just the happy path. Review the dialogue map, sample test cases, and the handover documentation before you decide.
The most common failures are vague goals, weak content, poor training data, and no plan for handoff to a human when needed. Conversational AI also fails when teams expect it to understand everything without guidance or integrations. Strong specialists reduce risk by narrowing the scope and testing early with real questions.
The average hourly rate of freelancers in Munich, Germany who have used Conversational AI in their recent projects is 92 €, which corresponds to a daily rate of about 733 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Conversational AI in their recent projects, 80% hold at least a Bachelor's degree and 60% hold at least a Master's degree.
On average, freelancers in Munich, Germany who have used Conversational AI in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 3.5 years.
The most common languages among freelancers in Munich, Germany who have used Conversational AI in their recent projects are German (100%), English (100%), and Spanish (33%).
The most common industries among freelancers in Munich, Germany who have used Conversational AI in their recent projects are Information Technology (100%), Media and Entertainment (67%), and Healthcare (50%).
The most common business areas among freelancers in Munich, Germany who have used Conversational AI in their recent projects are Product Development (100%), Information Technology (83%), and Business Intelligence (67%).
Main locations of FRATCH Experts, who have recently used Conversational AI
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Countries:
Berlin Hamburg 
Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
