Artificial Intelligence Experts
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Meet FRATCH Experts who have recently used Artificial Intelligence
Felix Bauchspiess
Last position:
Digital Consultant and Solution Manager at Vorwerk SE & Co. KG
Launch of a new digital product in the Chinese market as part of a global growth strategy.
Contact point and coordinating interface between central product management, local Chinese teams, and international stakeholders.
Managing the full program management for coordinating complex digital projects.
Successful launch of a digital product in China (including successful certification for the Chinese market).
Balancing local requirements with global priorities while taking tax and regulatory conditions into account.
Introducing a new way of working to improve collaboration and governance across locations.
Developing and implementing a scaling strategy for the digital business model in China.
Use of Jira, Confluence, Miro, Scrum, agile ways of working, SAFe.
Project language: English.
Marco Steidel
Last position:
IT Interim Manager & Digitalization Consultant at paarprojekt GmbH
- Project management and consulting services with a focus on IT interim management: digitalization of corporate management, including processes and applications
- Assessment of the entire IT infrastructure, including applications, core processes, and contracts, including cost optimization
- Evaluation and introduction of solutions to support digitalization in the company in the areas of property management, CRM, invoice review and approval processes, smart metering, DMS, and time tracking
- Digitization of file folders and introduction of SharePoint and Microsoft Teams as the central document and communication platform
- Design and delivery of an AI workshop, including rollout of AI tools to increase efficiency and transparency in key business processes
- Creation of training materials and delivery of user training for newly introduced digital processes and solutions
Ornel Franck Wora Yeno
Last position:
Sales Partner at ERGO PRO
- Industry: Insurance, Trade, IT
- Customers & Projects: Consulting and selling insurance and similar services
- Main tasks: Insurance consulting (health insurance, retirement planning, wealth building); commercial services, inside and field sales; sales data analysis and forecasting; customer consulting and support; opening a new sales headquarters for private and business customers; business development & innovation management; business use case development; process optimization; stakeholder management; team leadership and training; preparation and delivery of trainings;
- Technologies used: Microsoft Office 365, Microsoft Teams, Jira, Draw.IO, Camunda 8, Java (8, 17,21,25), Git, Spring Boot, Spring Batch, Spring Data REST, Spring Web, Spring Security, J-Unit, Playwright, Lombock, Vaadin, H2, PostgreSQL (16, 17 18), pgAdmin, Docker, LLMs, JasperSoft Studio, JasperReports
Jörg Kopitzke
Last position:
Exec. Coach / Consultant / Agilist at HASOMED GmbH
Repaired a broken “ScrumBan” process, then established a pure Kanban system; increased output in the Kanban flow by 22% within four weeks
Increased team autonomy and decision-making ability by implementing new decision strategies; resulting in up to 25% better outcomes
Redesigned retrospectives (including one-to-one coaching and workshops), which led to consistent implementation of the resulting action items
Intensive coaching of Product Owners (POs) to develop and support “Empowered Teams”, alongside leadership development to place agile frameworks and methods in a realistic context (“de-illusioning”)
Supported change management processes to promote an agile company culture among management and teams, improving internal communication to increase transparency and effectiveness in agile processes
Matthias KĂĽhnlein
Last position:
Business Owner at AKM
Management of multiple MFA methods for central authentication within a corporate group. Interface between various stakeholders such as support, finance, developers, and security departments. Budget controlling and monitoring of KPIs and SLAs. Review of operational documentation
Silvia BĂĽrmann
Last position:
Fractional VP Sales, Executive Sales Coach & GTM Advisor, AI Transformation Management at Self-employed
- Advise B2B technology and mid-market companies on commercial strategy, sales effectiveness, operating model design, and scalable growth.
- Coach senior sales leaders and executive teams on GTM choices, leadership effectiveness, accountability, and execution.
- Support market entry and growth planning through structured assessment of customer segments, value propositions, channel options, coverage models, investment priorities, KPIs, and risks.
- Facilitate peer-level strategy sparring and translate strategic decisions into measurable commercial initiatives.
- Combine systemic coaching, sales leadership experience, and change management practice to ensure decisions are practical and adopted.
Khalid El Mansouri
Last position:
Lead Architect & Developer at kem-consulting
Development of an agent-based governance platform for the automated assurance of EU AI Act compliance and ODA-compliant orchestration of AI services in complex enterprise environments.
Design and implementation of an agent-based "Mission Control" framework (Aletheia Conductor) for autonomous state monitoring and process control.
Development of "Compliance-as-Code" (CaC) solutions based on OPA/Rego for system-wide enforcement of regulatory guardrails.
Integration of TM Forum ODA standards (TMF630, TMF622, TMF642) to ensure interoperability and standardization.
Building a highly available event-driven architecture using Redpanda and CloudEvents v1.0 for near-real-time event processing.
Implementation of an audit-proof "Evidence Chain" through cryptographic linking of trace logs in preparation for automated audits.
Tech Stack: Java 21 (Quarkus Native), TypeScript (Next.js), Redpanda (Kafka API), CloudEvents v1.0, OPA (Open Policy Agent) & Rego, TimescaleDB, ZincSearch, Redis, TM Forum ODA, Git, GitHub, Clean Code Development, Like-C4.
Stefan Ojanen
Last position:
Founder at ProtocolEngine.io
Evidence-led health intelligence platform turning published research into personal health protocols. It scores 430 habits, foods, and supplements against the studies behind them, and moves the score when the evidence moves. Built solo.
- Built the daily ingestion pipeline across PubMed, bioRxiv, and medRxiv: 43,000+ papers from 3,400+ journals processed into 230,000+ typed evidence claims, each one traceable back to the study it came from.
- Designed the six-factor evidence scoring model and the public changelog behind it, so no recommendation ever appears without the papers underneath it. 23,000+ grade changes recorded and explained to date.
- Shipped an entity information model connecting every intervention to its mechanisms, biomarkers, and outcomes: 118 biomarkers with region-specific reference ranges, 77 mechanisms, 32 graded outcomes.
- Built the personalisation layer: blood panel ingestion that reads lab PDFs with a vision model and corrects results for draw time against the user's wake anchor, plus Oura, WHOOP, and Withings integration for daily readiness context.
- Operate eleven specialised review agents over the corpus and codebase, covering paper curation, retrieval quality, health-claim compliance across EU and US regimes, and security.
- Shipped the Evidence Assistant, a RAG assistant that answers from the claim database and cites the underlying papers, plus a B2B practitioner tier, an Expo React Native app, and localisation across 3 languages and 7 markets.
Stack: Next.js 16, TypeScript, Supabase, pgvector, Anthropic Claude, Vercel, DeepInfra.
Onur Kayir
Last position:
Project Manager & Outsourcing Manager at SENEC GmbH (EnBW Group)
- Setup of a scalable nearshore IT developer hub (Croatia, Czech Republic, Poland) as an independent company through a BOT model (Build – Operate – Transfer)
- Identification, selection, and management of full-service agencies; introduction of control and governance mechanisms including KPIs, SLAs, and regular service reviews
- Creation and review of data processing agreements and framework contracts in alignment with Legal & Compliance; integration of regulatory requirements (incl. KRITIS) into process design
- Consulting on cloud vs. on-premise strategies, data storage, and authorization concepts; support for procurement in vendor selection and provider assessments
- Change management and process harmonization between internal teams and nearshore partners; reporting to management, CFO, and CIO
Result: Scalable IT developer hub with an audit-proof governance model, reduced operating costs, and faster product development.
Tobias Witte
Last position:
CEO & Fouder at Wittbix
Shamaila Mahmood
Last position:
Founder/Kubernetes and Cloud Architect at Kubekanvas
- Developed a browser-based platform for Kubernetes no-code deployment and cluster management
- Developed a CLI in TypeScript to deploy resources in the cluster without leaving the browser UI.
- Implemented DevSecOps pipelines: image scanning, SBOM, policy enforcement, supply-chain security, and used Kyverno. Implemented IAM integration for the command-line utility tool.
- Designed role and permission models for Keycloak, OAuth/OIDC, and social login flows.
- Used LLMs to convert user intent into diagrams.
- Worked on integration with multiple sovereign clouds like StackIT, Hetzner, CIVO, UpCloud, plus public clouds like AWS, GCP, and Azure
- The technology stack includes Java, Spring Boot, Kubernetes, OpenAI, Kubernetes multi-tenancy using vCluster, Karpenter, RBAC for CLI, Helm, React
Peter Schillen
Last position:
Senior ML Engineer & AI Researcher at Anonymous client
Project: Defect generation on inspection images of metal surfaces
Environment:* Automated Visual Inspection (AVI), Metallurgy & Manufacturing
Goal & implementation: Concept, architecture, and training of Generative Adversarial Networks (Pix2PixHD / SPADE) for image-to-image transformation. Targeted generation of synthetic material defects (e.g. cracks, inclusions, scale) on rough metal surfaces under real inspection-light conditions for privacy-compliant and efficient dataset expansion (Data Augmentation).
Technical design: Implementation of robust Generative AI and Computer Vision pipelines in Python and PyTorch. Use of semantic segmentation approaches for mask-guided defect synthesis and downstream evaluation with EfficientDet object detection models.
Business impact: Massive dataset upscaling (factor of 10x) without time- and cost-intensive physical inspection runs, while at the same time drastically improving the detection performance of automated inspection systems.
Technologies & skills used: Python | PyTorch | SPADE | Pix2PixHD | EfficientDet | Machine Learning | Semantic Segmentation | Computer Vision
Tobias Mönch
Last position:
Power BI Expert at MID-SIZED RETAIL COMPANY FOR CLEANING TECHNOLOGY AND HYGIENE PRODUCTS
Reporting and controlling with Power BI for a productive ERP system
- Analysis of ERP data and interfaces for use in Power BI dashboards
- Evaluation and migration of existing reports (e.g. Excel) to Power BI
- Development of an access rights concept for selective data access
- Documentation and training on how to use and adapt the Power BI dashboards
Label: Power BI, Excel, SelectLine ERP, Microsoft SQL, SQL Server Management Studio
Sascha Bach
Last position:
Freelance at GxPlex
- Built a custom MediaWiki instance including installation, MySQL database, SSL, and automatic backups
- Set up user roles (Admin, Mod, Verified, User) and a permissions system
- FlaggedRevisions for editorial review workflow · comment and rating extensions
Beate Peters
Last position:
Interim Head of Service at Altendorf Group
- Strategic and operational leadership of the technical service organization
- Improvement of all processes and workflows
- Development and introduction of a service management IT tool incl. AI database, customer app, and self-service portal
Discover over 15,000 top freelancers
Statistics of experts using Artificial Intelligence
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
3.1 years
Positions per freelancer
10
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Professional Services, Manufacturing
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
93%
Master's degree or higher
63%
Doctorate
11%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
97%
Based on our profile pool as of 6 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology 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 using Artificial Intelligence
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 6 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it covers
Artificial Intelligence turns data into systems that can classify, predict, recommend, generate, and automate decisions. Companies bring in specialists for chatbots, document processing, search, forecasting, and decision support. The work often sits inside product teams, data teams, or automation projects.
Core skills
Strong professionals usually combine model design with practical delivery. They know how to work with data, choose suitable algorithms, test outputs, and integrate AI into software that people can use.
- Machine learning model design and evaluation
- Prompting and working with generative AI
- Data preparation and feature engineering
- API integration and deployment
- Monitoring, tuning, and quality checks
Typical use cases
Artificial Intelligence is used where rules alone are too limited. Common tasks include customer support automation, content generation, fraud detection, recommendation engines, and predictive analytics. In many projects, the goal is not a fully autonomous system, but a reliable assistant that improves human work.
Ecosystem and tools
The ecosystem is broad. It often includes Python, TensorFlow, PyTorch, scikit-learn, OpenAI models, vector databases, cloud services, and MLOps tools. Good experts understand when to use standard ML, when to use large language models, and when a simpler approach is safer and easier to maintain.
When companies hire help
Teams usually need freelance support when a prototype must become a production system, when internal skills are missing, or when a project needs an outside review. They also bring in experts to improve model quality, reduce latency, clean up data, or connect AI features to existing software. This is common in fast-moving product work and in regulated sectors.
What strong experts do
Strong Artificial Intelligence specialists do more than train models. They define the problem clearly, check data quality, measure results, and explain trade-offs in plain language. They also think about privacy, bias, security, and how the system behaves after launch.
Frequently asked questions
Before you brief your next project: the most common questions about Artificial Intelligence.
Artificial Intelligence is used to automate tasks that need prediction, language understanding, pattern recognition, or content generation. In practice, that includes support bots, search, recommendations, document review, forecasting, and fraud detection. The best experts focus on a clear business task, not on using AI for its own sake.
AI is the broad field. Machine learning is one way to build AI systems, and generative AI is a newer family of tools that creates text, images, code, or other content. Companies often need professionals who understand all three, because the right choice depends on the use case and the data.
A strong Artificial Intelligence freelancer usually brings data handling, model evaluation, product thinking, and solid software integration skills. Many projects also need Python, cloud services, prompt design, and MLOps basics. If the work involves language or search, vector databases and retrieval methods are often important too.
Artificial Intelligence work starts best when the goal, data source, and success criteria are clear. A freelancer can help shape those if needed, but the team should be ready to share sample data, existing systems, and constraints. Without that context, even a strong expert will spend time guessing instead of building.
For simple prototypes, a broad Artificial Intelligence specialist may be enough. For production systems, look for someone who has shipped similar work, especially around your domain, data type, and deployment setup. The more risk, compliance, or integration work involved, the more useful deep specialization becomes.
Yes, Artificial Intelligence work is often remote-friendly because much of it depends on code, data access, and clear communication. On-site time can help during workshops, sensitive data reviews, or early discovery with stakeholders. Many teams use a remote-first setup and bring people together only when needed.
A good AI specialist can explain why a model or approach was chosen, how it was tested, and what failure modes remain. Look for evidence of clean data handling, honest evaluation, and a plan for monitoring after launch. If the explanation is vague or the metrics do not match the use case, that is a warning sign.
Artificial Intelligence projects often need data engineering, backend integration, cloud architecture, product design, and security awareness. For language-based systems, search and retrieval are common companions; for forecasting or classification, analytics and experimentation matter more. The best freelancers know how to work with these nearby disciplines instead of treating AI as isolated work.
The average hourly rate of freelancers who have used Artificial Intelligence in their recent projects is 105 €, which corresponds to a daily rate of about 841 € based on an 8-hour working day.
Of the freelancers who have used Artificial Intelligence in their recent projects, 93% hold at least a Bachelor's degree, 63% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers who have used Artificial Intelligence in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 3.1 years.
The most common languages among freelancers who have used Artificial Intelligence in their recent projects are German (98%), English (97%), and French (21%).
The most common industries among freelancers who have used Artificial Intelligence in their recent projects are Information Technology (81%), Professional Services (51%), and Manufacturing (38%).
The most common business areas among freelancers who have used Artificial Intelligence in their recent projects are Information Technology (82%), Product Development (74%), and Project Management (65%).
Main locations of FRATCH Experts, who have recently used Artificial Intelligence
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.
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