Data Pseudonymization Experts in Germany

AI Assistance and Target Vision for Partially Autonomous Energy Portfolio Management

Building an AI control layer directly on the up-to-date daily live portfolio of a large energy provider — not as an isolated pilot, but as an operational extension of the existing DB1 and portfolio management. The goal is the gradual development from assistance through monitoring/alerting to analysis agents with Human-in-the-Loop approvals, supplemented by a role-specific System of Engagement alongside the BI System of Record. At the same time, the business case, target vision and management pitch compared with static monthly reporting are being developed.

• AI control layer: Design and build on the existing live portfolio data product (several million contracts) — development stages assistance → monitoring/alerting → agents with Human-in-the-Loop approvals.
• LLM-supported data analysis: Semantic queries, SQL/tool integration and additional RAG components based on portfolio, plan-versus-actual and data quality data (Azure OpenAI, Snowflake), with drill-downs to individual contract level.
• Analysis agents: Multi-stage agents for variance and driver analyses of churn, price adjustments, volumes and procurement costs.
• Views concept: Role-specific interfaces for business units, management and C-level as a System of Engagement alongside the BI System of Record.
• Business case & pitch: Target vision and cost-benefit argumentation compared with static monthly reporting.
• LLM setup (privacy & security): Coordination with IT Security and Data Protection — EU region, data separation and approval processes.
• Agent architecture: Multi-stage agent pipelines (analysis → validation → summary) with documented data sources, tool calls, review steps and source references for each statement.
• Data foundation: Built on the up-to-date daily DB1 data product (Snowflake, dbt) — portfolio, plan-versus-actual and data quality metrics as the common basis for all AI analyses.
• Guardrails & evaluation: Evaluation and approval processes for LLM responses relating to management-relevant statements — test sets, metrics and human review.
• Prototyping & validation: Iterative validation of agent responses with the business unit — test question catalogue, feedback loops and response quality for each release.
• Roadmap & development stages: Detailed stages from assistance → monitoring/alerting → partially autonomous management, including transition criteria and governance for each stage.
• Integration: Integration into the existing BI and data landscape — BI remains the System of Record, while the AI layer provides interactive drill-down paths as the System of Engagement.
• Enablement: Enablement of business users — prompting guides, training and an operating model for ongoing use.
• Management: Coordination of business units, Data Engineering, IT Security and Data Protection.
• Change Management: Communication and expectation management with business units and management throughout the development stages.

Results:

• Built on an existing up-to-date daily data product with several million contracts
• Established an LLM setup coordinated with Data Protection and IT Security in the EU region, including data separation and approvals
• Defined three development stages through to partially autonomous management
• Designed role-specific views for business units, management and C-level
• Developed the business case and management pitch for the development stages
• Established an iterative response-quality validation process with the business unit
• Designed the operating model for assistance operations and initiated validation

Stack: Azure OpenAI, Azure AI Foundry, Snowflake, dbt, React, TypeScript, Entra ID, RAG, Agentic AI, analysis agents, Human-in-the-Loop, Prompt Engineering, LLM Evaluation, LLMOps, GDPR / EU region, Azure DevOps, Python, SQL, Change Management

• Hands-on product and portfolio analyses with actionable recommendations
• Skilled in consulting, concept development, and agile project management
• Technical leadership & team empowerment – for smooth agile delivery with foresight and guardrails

• Developed web applications and backend services for secure environment of GEMATIK as basis for applying and managing digital medical professional IDs, focusing on highest security standards
• Implemented current frontend technologies, runtime configurable features, and automated delivery in a microservice architecture using Helm charts and GitLab deployment pipelines
• Technologies: React, TypeScript, Java, Spring Boot, Docker, Kubernetes, Helm, Tailwind CSS, OpenShift

• Finalization of the information register and ICT asset management
• ICT service provider analyses including sub-service providers
• Contract analyses with assessment of protection needs and system integration architecture
• IDV, kwF and mapping of approval-requiring activities and processes

• Agile requirements management according to consultation guidelines
• Development of a master data system
• Preparatory activities for audits
• Managing the development team for the creation of microservices for billing preparation and execution
• Designing connections to various internal and external interfaces
• Designing release cycles and planning emergency management

• Developed automated ETL pipelines with AWS Glue and Athena to ensure consistent data quality and governance requirements
• Implemented validation, anonymization, and encryption measures for data in compliance with GDPR
• Optimized cloud costs by introducing FinOps practices and increased transparency for business units
• Monitored performance, performed root cause analyses, and ensured adherence to SLAs
• Supported data and solution architects in building scalable data models for ML and analytics scenarios