
Artificial Intelligence Experts in Berlin
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Meet FRATCH Experts in Berlin, who have recently used Artificial Intelligence
William N.
Last position:
Power BI Solutions Architect/Engineer & AI Consultant at AVERDUNG GmbH
- Redesign of the company's BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment featuring a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic into a central semantic model – eliminating redundant files, manual data transfers, and inconsistent metrics between departments
- Forecasting & planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enables rolling forecasts and continuously up-to-date cash flow transparency for management
- Optimization of existing Power BI dashboards in terms of performance, structure, and analytical value using an AI-native approach
- Analysis and improvement of the data model, including data quality analyses, data cleansing, and consistent modeling using star schema, DAX, and Power Query
- Incident & anomaly analysis: Identification, investigation, and explanation of data anomalies, including root-cause analysis and concrete recommendations for action
- AI solution architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Creation of a historical data layer as a basis for trend and time-series analyses
- AI-supported automation: Design and development of AI skills, agents, loops, and processes for the automated analysis and interpretation of reports
- Automated reporting workflow: Setup of scheduled, automated email distribution of AI-generated analyses and recommendations to stakeholders
- Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
- Breaking down overall requirements into clearly defined work packages and tasks
- Definition, prioritization, and management of milestones throughout the entire project lifecycle
Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code
Paul K.
Last position:
Program Manager – Multi-Project Operational Stabilization (Operational Excellence) at ITDZ - IT Service Center Berlin
- Overall leadership of several strategic operations projects focusing on Workplace Services, SLA Framework, access management, certificate management, e-learning, backup & recovery, test management, and capacity management, as well as the introduction of system monitoring and feasibility studies for 24x7 operations, in some cases including implementation in ServiceNow
- Creation of various ServiceNow operating concepts covering training, access rights, and emergency management as part of a new cloud hosting initiative for the ServiceNow platform
- Executive board reports and leadership of steering committees as part of company-wide strategic objectives, as well as the establishment of new balanced scorecards for measuring KPIs related to optimization-driven project results
Silvia B.
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.
Stefan O.
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.
Sascha B.
Last position:
Web Developer at GxPlex
- Built a customized 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 workflows · Commenting and rating extensions
Chris W.
Last position:
Senior Strategy Advisor, Transformation Lead – program realignment with target picture, governance, and priority steering at Sparkassen-Finanzgruppe | S-Communication Services
In-house consulting provider and driver of transformation within the group, multi-stakeholder environment and C-level.
Realignment and stabilization of a cross-functional transformation and scaling program within the group. Sharpening the target picture, priorities, and set of measures, as well as building reliable governance, planning, and steering structures. Structuring roles, responsibilities, and strategic initiatives while including AI and IT automation ideas.
Designed program realignment and project portfolio management
Developed strategy model and target picture for IT projects
Structured portfolio, roadmap, and priorities
Established governance and regular meetings
Worked out operating model for flagship projects
Assessed AI and automation ideas
Clarified roles and responsibilities
Implemented change measures
Developed, moderated, and evaluated workshops
Transformed 17 initiatives into a steering model
Increased transparency and decision-making ability
Strengthened commitment in steering
Sharpened the operating model structurally
Integrated three top-5 institutes
Involved over 80% of stakeholders
Governance
Portfolio steering (PPM)
Change management
Artificial intelligence
Workflow automation
AI use case assessment
Confluence
Jira
Stakeholder management
Chintan P.
Last position:
Product Owner and Technical Product Lead at Sustamize GmbH
LLM-based features for automated CO₂e data extraction from unstructured documents (70% reduction)
Agentic AI pipeline for automated Scope 3 emissions calculations with 150.000+ validated data records
Intelligent API workflows for real-time carbon footprint calculations in ERP and ESG systems
ML algorithms for predicting emissions hotspots and optimizing product design
Automated data validation pipelines with NLP for quality assurance of CO₂e datasets
Led a 15-person cross-functional team in developing 10+ AI features
Strategic product planning and AI roadmap with 35% shorter time-to-market
Stakeholder management with DAX companies (40% higher satisfaction, 95% retention)
On-time project delivery with 95% budget adherence through data-driven backlog management
Agile methods (Scrum, Kanban) with continuous AI/ML integration (25% increase in team velocity)
Product-market fit for AI features through A/B testing and analytics (60% higher adoption rate)
Dmitry P.
Last position:
Freelance Digital Marketing Analyst at Freelance
- Marketing Strategy: Lead the end-to-end analysis and evaluation of cross-channel marketing campaigns across the entire Customer Journey. My focus is identifying optimization potential and deriving clear, actionable recommendations that drive measurable business impact.
- Data Science & AI: Advanced predictive modeling (Churn, LTV), market basket analysis, clustering, and real-time AI-powered audience discovery utilizing RAG/LLMs.
- Marketing Analytics & Measurement: End-to-end attribution analysis, Marketing Mix Modeling (MMM), audience segmentation, conversion path analysis, and A/B testing across all major platforms.
- Data Engineering & Reporting: Designing and managing robust, multi-platform data pipelines (BigQuery, GCP) for data consolidation, automated dashboard generation, and critical API integrations.
Abdulla A.
Last position:
Principal AI Product Consultant at Recare
- Shipped Recare Voice Desktop from 0 to 1 in two months, including multi-language clinical documentation that auto-transcribes into structured German medical notes.
- Reduced LLM inference costs by 60–70% across Docs and Extract through prompt caching architecture.
- Built the AI workbench used by PMs/engineers for prompt experimentation and the Langfuse eval stack (10k+ traces evaluated).
Gilad G.
Last position:
European Strategy Atlas – Independent Analytics & Decision-Support Project at Independent Project
Designed and built an end-to-end interactive decision-support application using public European data across 27 EU countries and multiple strategic dimensions. Developed a structured analytical methodology for comparing countries, identifying patterns and trade-offs, and exploring strategic choices rather than presenting static dashboards. Translated complex multidimensional data into guided interactive exploration and learning workflows for non-specialist users. Built the application end-to-end using Python and Streamlit, with AI-assisted development and Git-based version control. Developed the project independently from problem framing and data analysis through methodology, UX logic, implementation and deployment.
Tools: Python, Streamlit, Git, AI-assisted development
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Hubertus S.
Last position:
Senior Product Manager AI
Workflow-automation SaaS for operations teams (Berlin, 120 people); full-time freelance engagement reporting to the CEO: an initial 12-month interim mandate, extended twice through the AI build-out; owned product for one squad and coached the other product managers on process.
- Led generative AI (LLM) integration into the core product: from LLM-powered steps to natural-language workflow authoring and step-level automation suggestions, plus AI-managed dynamic workflows, shipped behind eval gates with human-in-the-loop fallbacks: AI-drafted workflows grew to 31% of all new workflows, and median time-to-first-workflow fell from 3 days to 4 hours.
- Packaged the AI capabilities as a usage-based add-on priced on executed automation steps, working with sales and marketing on positioning: ~€800K added ARR in the first year, and adopting accounts churned 1.8 pp less.
- Owned the roadmap end to end: replaced feature-request-driven quarterly planning with an outcome-based rolling roadmap built on quarterly bets and explicit kill criteria, presented monthly to the executive team and quarterly to the board.
- Rebuilt the product-management operating system: weekly customer-discovery cadence incl. workshop facilitation, RFC/decision-doc reviews and a single quarterly metrics narrative; coached four product managers, one promoted to senior during the engagement.
- Closed the engagement as scoped: hired and onboarded the permanent VP Product, handed over the process playbook and roadmap, and exited on schedule in June 2026.
Anjana R.
Last position:
Senior Product Designer at Casavi GmbH
I served as the Lead Designer for two cross-functional teams at Casavi, a software platform for property managers. Casavi is a central platform for all aspects of digital property management, which streamlines operations and business processes.
SmartTask: The team focuses on ticket management, workflow automation, AI integration, enhancing communication between property managers and their clients.
Customer app/portal: The team is dedicated to fostering community engagement among residents of managed properties. The customer portal in combination with the Casavi app solves the challenges for property and facility managers.
My role spans the full design lifecycle, covering UX/UI design, user research, usability testing, and strategic design planning, across Casavi's web platform, mobile app, and customer portals. Each team comprises around 10 members, including a project manager, designer, developers, and QA testers. I am also responsible for the accessibility assurance of the whole product.
Design unit role: In addition to my core responsibilities, I actively contribute to the development and maintenance of the company's design system and style guide ensuring consistency and scalability across all products. Mentor junior designers is my official and moral responsibility.
Patrick H.
Last position:
Lead Technical Recruiter | Business Partner AWS EMEA at Amazon Web Services (AWS)
- Partnered with senior stakeholders across AWS EMEA to drive talent strategy, partner development, and business growth in the cloud ecosystem.
- Focus areas:
- Collaboration with Sales & Partner Management on Go-to-Market initiatives
- Advisory on long-term resource strategy for Cloud, Data, and Security Divisions
- Supporting internal innovation teams in scaling AI and automation projects
- Result: Contributed to AWS’s expansion in Central Europe by aligning business, technology, and people strategy.
Anish G.
Last position:
GTM Intelligence Engine · Open Source
- PROBLEM: GTM effort is guesswork across fragmented identities and channels, with no closed feedback loop.
- BUILT: Cost-pyramid engine (L0–L3): identity resolution across ~25k entities, explainable intent scoring, and a closed decision loop (propose → execute → evaluate → learn) with calibration.
- IMPACT: Shipped v1.3.1 with a live demo; 99% of operations resolve at the free L0 tier (CI-enforced); $0 to run without any API key.
Myrto P.
Last position:
UX Lead, Strategist for Property Management Systems at Destination Solutions
- Leading UX for a Property Management System, an all-in-one solution for vacation rental agencies and tourism regions, covering marketing and rental of holiday apartments and houses
- UX audits, conception, and implementation of UX strategy with a focus on regulatory, security, and user-centered requirements
- Advising C-level stakeholders on UX strategy and design best practices
- Planning and conducting research with agencies and property owners
- Design system strategy and definition of UX architecture
Discover over 15,000 top freelancers
Statistics of experts using Artificial Intelligence
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 18 years)

Position duration
2.5 years (Germany: 3.1 years)

Positions per freelancer
9 (Germany: 10)

Top business areas
Product Development, Information Technology, Project Management

Top industries
Information Technology, Professional Services, Banking and Finance

Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
96% (Germany: 93%)
Master's degree or higher
64%
Doctorate
8% (Germany: 11%)

Certifications per freelancer
2 (Germany: 3)

Most common languages
English, German, French

Speak two or more languages
95% (Germany: 97%)
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Berlin 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 Berlin 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Artificial Intelligence 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 (85%)
- Professional Services (51%)
- Banking and Finance (40%)
- Education (37%)
- Retail (35%)
- Media and Entertainment (33%)
- Healthcare (31%)
- Automotive (27%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Artificial Intelligence delivers
Artificial Intelligence enables software to interpret data, recognize patterns, generate content and support decisions. Companies use it for recommendation systems, conversational interfaces, document processing, forecasting, fraud detection and autonomous workflows. Projects may combine predictive models with generative AI, natural language processing or computer vision.
Models and applications
- Train and evaluate supervised, unsupervised and deep learning models
- Build retrieval-augmented generation and conversational systems
- Extract meaning from text, images, audio and video
- Add classification, forecasting or recommendation features to products
- Connect models to APIs, databases and internal workflows
The right approach depends on the data, risk, latency and level of human oversight required. Strong specialists choose practical model architectures instead of adding AI where a simpler rule-based solution is more reliable.
Ecosystem and tooling
Artificial Intelligence work often includes Python, PyTorch, TensorFlow, scikit-learn, Hugging Face and vector databases. Specialists may also use cloud services, model APIs, notebooks, data pipelines, Docker and Kubernetes for deployment. They establish evaluation sets, prompt or fine-tuning workflows, monitoring and version control so models remain useful after launch.
When companies need expertise
Companies bring in freelance professionals when they need to validate an AI use case, turn a prototype into a dependable product or improve an existing model. A specialist can also assess data quality, select an appropriate model provider and set up an operating process for experiments and releases. In Berlin, local teams may benefit from on-site workshops alongside remote delivery across product, data and engineering functions.
Reliable production systems
Good Artificial Intelligence work is measurable, explainable where necessary and designed around real user needs. Experienced professionals define success criteria, test for bias and failure cases, protect sensitive data and document limitations. They also plan for inference costs, response time, fallback behavior and monitoring rather than stopping at a convincing demo.
Choosing the right professional
Look for evidence of a complete delivery cycle: problem framing, data preparation, model selection, evaluation, integration and production support. Ask how the specialist handles weak data, changing inputs and uncertain model output. Language expectations matter for text systems, especially when a Berlin project serves German-speaking users; domain knowledge and clear communication are just as important as framework familiarity.
Frequently asked questions
Not sure where to start with Artificial Intelligence? These answers cover the essentials.
Artificial Intelligence is used for systems that classify information, predict outcomes, understand language, interpret images or generate text and other media. Common deliverables include recommendation features, support assistants, document extraction, forecasting tools and workflow automation.
Artificial Intelligence learns patterns from data or uses trained models to handle inputs that are difficult to describe with fixed rules. Traditional automation follows explicit instructions, while AI is useful when interpretation, prediction or generation is required. Many reliable products combine both approaches.
A strong Artificial Intelligence specialist often combines Python, statistics, data engineering, cloud deployment and software integration skills. Experience with model evaluation, data privacy, prompt design, vector search or MLOps can be important depending on the project.
The required experience depends on the risk and complexity of the use case, not simply on the model selected. A proof of concept may need focused experimentation, while a customer-facing Artificial Intelligence system requires production integration, monitoring, security controls and a plan for unreliable output.
Yes. Artificial Intelligence projects can be delivered remotely when data access, decision ownership and evaluation criteria are clear. On-site workshops in Berlin can help align product, data and compliance stakeholders, while regular remote sessions support implementation. German-language capability may matter when the system processes local customer or business content.
Ask the Artificial Intelligence specialist to explain the problem definition, data assumptions, evaluation method and failure handling in plain language. Review a relevant delivery example and check whether they measured real user outcomes rather than presenting only a model demo.
Generative AI is suited to producing or transforming content, such as drafts, summaries, answers and structured text from documents. Predictive models are usually a better fit for scoring, classification or forecasting. The choice should follow the desired output, data quality and tolerance for incorrect results.
Before engaging an Artificial Intelligence professional, define the business decision or user task, available data, success measures and required integrations. Also clarify access permissions, human review, deployment ownership and how the system will be monitored after release.
The average hourly rate of freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects is 103 €, which corresponds to a daily rate of about 828 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects, 96% hold at least a Bachelor's degree, 64% hold at least a Master's degree, and 8% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects are English (98%), German (95%), and French (18%).
The most common industries among freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects are Information Technology (85%), Professional Services (51%), and Banking and Finance (40%).
The most common business areas among freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects are Product Development (79%), Information Technology (79%), and Project Management (60%).
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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