
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
Fred K.
Last position:
Project Manager Digital Restructuring at Northrop Grumman LITEF GmbH
Assignment focus: Leading digital restructuring in a highly regulated Defence and Aerospace environment. Focus areas: improving data flows and data quality, introducing paperless data collection in production, integrating machine data for automatic SPC calculation and process control, as well as cybersecurity analyses.
Main objectives:
- Analyze, structure and improve data flows and data quality in production
- Introduce paperless data collection in manufacturing areas
- Integrate machine data for automatic SPC data calculation and process control
- Implement digital restructuring while meeting regulatory requirements in the Defence environment
Measures and results:
- Analyzed and structured existing production data flows as a basis for control and reporting
- Established mechanisms to ensure data quality and availability across manufacturing areas
- Introduced paperless data collection in production — replacing manual and paper-based processes
- Integrated machine data for automatic SPC data calculation (control charts, Cp/Cpk) and real-time process control
- Conducted cybersecurity analyses in the production and IT environments
Area of responsibility: Project management for digital restructuring, paperless production, data management and data quality in a highly regulated Defence and Aerospace environment.
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
Greta S.
Last position:
Project Lead for a transformation consulting project in Saudi Arabia at Government Ministry
Led a six-person multidisciplinary team delivering an 18-month organizational transformation program. Designed governance and decision-making structures, roles and responsibilities, capability- and knowledge-building approaches, learning interventions, and communication and implementation plans, and supported their execution to embed new ways of working across the ministry.
- Led a six-person multidisciplinary team delivering an 18-month organizational transformation program
- Designed governance, decision-making structures, roles and responsibilities
- Developed capability- and knowledge-building approaches and learning interventions
- Created communication and implementation plans
- Supported execution to embed new ways of working across the ministry
Marcus B.
Last position:
Senior PMO Lead / Transformation Office Consultant at International Family-Owned Company
International Family-Owned Company | Revenue of more than 1 billion EUR | CONFIDENTIAL
- Established and operationalized a company-wide PMO; took over the initial management function during ongoing operations.
- Structured a portfolio of more than 15 strategic transformation initiatives across several countries and functions.
- Designed project intake, decision levels, responsibilities and regular steering meetings; management reporting as well as risk and dependency management.
- Established the PMO environment with Microsoft 365, Planner Premium, Teams, SharePoint and Forms; planned reporting and prepared the structured handover to an internal PMO organization.
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.
Inka S.
Last position:
Freelance Recruiter & HR Operations at D-LABS GmbH
- Independently managing recruiting for design, research, and freelancer positions
- Successfully filling three key positions in UX Design and User Research in close collaboration with the hiring managers
- Further developing recruiting processes and optimizing the candidate experience
- Developing standardized recruiting templates, HR documentation, and process guides
Franziska N.
Last position:
Strategic and Operational Business Partnering & Project Management | Organizational Transformation
- Further development and harmonization of cross-site HR structures and processes to increase efficiency and governance in close, ongoing collaboration with the (Group) Works Council.
- Management of the HR transformation during the change of ownership and realignment of the holding structures, generating annual savings of around €1.5 million
- Strategic development and restructuring of the Finance function with the CFO, establishment of a performance culture and optimization of structures and processes with a positive P&L impact.
- Realignment of Talent Acquisition, reducing time-to-hire from 7 months to 8 weeks, optimizing the cost and supplier structure, and introducing data-based management
Viliana H.
Last position:
Trainee in Insurance Management at Allianz Deutschland AG
Worked across several departments with a focus on AI implementation, change, strategic projects, and leadership development.
- Implemented AI initiatives and change management projects.
- Supported strategic analyses and prepared decision-making materials for top management.
- Prepared and facilitated leadership meetings and offsites.
- Developed controlling solutions with Excel for structured management and analysis.
Bidya B.
Last position:
Product Manager – Payments & Platform at Pipedrive
CRM and revenue platform managing billing and subscription workflows.
- Scaled payments infrastructure across data products, direct debit expansion and automated abuse prevention, generating $416K in annualized operational savings ($8K/week) by eliminating redundant gateway calls.
- Owned backlog and sprint execution for autonomous checkout abuse detection pipelines, designing real-time risk guardrails and velocity heuristics that blocked card testing attacks.
- Architected enterprise billing migrator user stories and data reconciliation mechanisms, achieving zero-downtime subscription state transitions and cutting $60K in infrastructure overhead.
- Expanded European direct debit (SEPA) payment capabilities, managing cross-squad API dependencies and automated webhook error-handling to eliminate checkout friction.
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
Information Technology, Product Development, 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
63%
Doctorate
8% (Germany: 10%)

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 9 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Berlin are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging 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 9 Oct 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 (86%)
- Professional Services (51%)
- Banking and Finance (39%)
- Education (37%)
- Retail (36%)
- Media and Entertainment (33%)
- Healthcare (31%)
- Automotive (28%)
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 826 € 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, 63% 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 (86%), Professional Services (51%), and Banking and Finance (39%).
The most common business areas among freelancers in Berlin, Germany who have used Artificial Intelligence in their recent projects are Information Technology (78%), Product Development (78%), and Project Management (59%).
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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