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Rickard Sörlin

The journey

From industrial systems to AI-enabled products

Portrait of Rickard Sörlin

Rickard Sörlin

Digital Platforms · Product · Applied AI

Stockholm, Sweden

My professional foundation comes from working close to real systems, customers and operational constraints.

I started as a customer-facing Project Engineer working with requirements, system design, programming, integration, commissioning and end-to-end implementation. I later became a national digital-platform technical expert, supporting customers and field teams while working close to platform quality, product lifecycle, QA, release validation and deployment readiness.

As Senior Technical Advisor, my work increasingly connected customer needs, project delivery, technology and business. I led technical discovery, translated customer and operational requirements into scalable architectures and solution directions, held end-to-end technical ownership and helped evaluate product and solution alternatives by balancing technical feasibility, lifecycle risk, reliability, cost and commercial value.

Alongside that professional journey, I deliberately expanded my capabilities through Computer Science, Interaction Design, applied AI, Innovation Management and postgraduate studies in Product Management, Product & Portfolio Strategy, Requirements, Strategy & Business Models and Leadership.

The common thread has been understanding the real problem and turning it into something useful, feasible and valuable.

Customer & Business

  • Customer Needs
  • Operational Reality
  • Business Value
  • Commercial Trade-offs

Product & Lifecycle

  • Requirements
  • Product Feedback
  • Release Readiness
  • Prioritisation

Technology & Delivery

  • Architecture
  • Technical Feasibility
  • Integration
  • End-to-End Ownership

AI & Human-Centred Design

  • Applied AI
  • Product Discovery
  • Interaction Design
  • User Validation

Product philosophy

The value of an AI product does not come from AI alone. It comes from solving the right user problem, understanding the available data, respecting operational reality, making sound technical and commercial trade-offs, and creating value people can actually use.

ProfessionalDevelopment

  1. 2003–2013· Professional

    Project Engineer — Digital Platforms

    Schneider Electric

    Customer Needs · Requirements · Delivery Reality

    Customer-facing engineering and digital-platform delivery, translating real customer and operational needs into workable system designs and taking technical responsibility through implementation and operational handover.

    • Worked directly with customers, end users and operations teams to understand needs, workflows and operational constraints, translating them into implementation-ready requirements and system designs.
    • Held end-to-end technical responsibility from solution design and programming through integration, commissioning, testing and operational handover, building strong judgement around feasibility, usability, reliability and maintainability.
    • Used delivery experience and QA findings to improve platform quality, integration patterns and maintainable solution design.
    • Customer Needs
    • Requirements
    • End-to-End Delivery
    • Technical Feasibility
    • Platform Quality

  2. 2013–2020· Professional

    Support Engineer — Digital Platforms

    National Technical Expert — Sweden

    Schneider Electric

    Customer Insight · Product Lifecycle · Release Readiness

    National technical expert connecting real customer and field experience with platform quality, product lifecycle and release readiness.

    • Translated recurring customer and field issues into structured product feedback, enhancement proposals and usability improvements, considering customer impact, market needs and business value.
    • Worked close to the product lifecycle through QA testing, release validation, defect identification and deployment / release readiness, evaluating new and changed functionality from a real-world customer perspective.
    • Connected national platform expertise and customer insight with technical feasibility to support product quality, adoption readiness and roadmap-relevant improvement decisions.
    • Customer Insight
    • Product Feedback
    • Product Lifecycle
    • Release Readiness
    • Enhancement Proposals

    Selected product / platform capability

  3. 2020–2025· Professional

    Senior Technical Advisor — Digital Platforms

    Schneider Electric

    Discovery · Product / Solution Options · Business Value

    Customer-facing technical leadership at the intersection of discovery, architecture, project delivery and business value.

    • Led customer-facing technical discovery and translated customer, operational and project needs into structured requirements, alternative architectures and scalable solution directions.
    • Worked across customers, sales, engineering and management to evaluate product and solution options while balancing customer value, technical feasibility, lifecycle risk, cost and commercial value.
    • Held end-to-end technical ownership and influenced prioritisation, product selection and architectural trade-offs to reduce delivery and lifecycle risk and shape feasible, scalable outcomes.
    • Customer Discovery
    • Requirements
    • Product / Solution Options
    • Technical-Commercial Trade-offs
    • Lifecycle & Risk

    Selected work during this role

  4. Parallel professional & academic development

    Professional and academic development overlapped in calendar time; some study periods were undertaken during leave of absence from the professional role.

  5. Completed before Aug 2025· Development

    Computer Science / Intelligent Systems

    Mälardalen University

    Degree of Bachelor of Science in Computer Science with Specialization in Intelligent Systems

    B.Sc. in Computer Science · Applied Artificial Intelligence

    Applied AI · Human-Centred Design · Research

    Bachelor of Science in Computer Science with a specialisation in Intelligent Systems, developed alongside professional employment with periods of leave of absence for studies.

    Rickard Sörlin with thesis colleagues and examiners at Mälardalen University
    Degree project completed — Mälardalen University

    Development work

    Selected AI & software engineering coursework

    Mälardalen University

    Artificial Intelligence 1

    • AI Methods
    • Problem Solving
    • Intelligent Systems

    Mälardalen University

    Artificial Intelligence 2

    • Advanced AI Methods
    • Reasoning
    • Applied AI

    Mälardalen University

    Advanced Machine Learning

    • Machine Learning
    • Modelling
    • Evaluation

    Mälardalen University

    Deep Learning

    • Neural Networks
    • Model Training
    • Applied Deep Learning

    Mälardalen University

    Software Engineering for AI

    • AI System Development
    • Technical Feasibility
    • AI Lifecycle

    2024 · Interaction Design

    2025 · Applied AI

    2025 · Bachelor thesis

  6. Aug 2025 – Jul 2026· Development

    Advanced AI · Innovation · Product Development

    Linköping · Umeå · Skövde · Blekinge Institute of Technology

    Product Management · Strategy · Advanced AI

    A coordinated postgraduate development period across several universities, covering advanced artificial intelligence, Innovation Management, Industrial Economics, Product Management, Product & Requirements Management, Strategy & Business Models, Agile Process & Project Management and Leadership.

    Universities, formal studies and product work

    Phase 1 · Aug 2025 – Jun 2026 · Advanced AI Foundation

    Aug 2025 – Jan 2026

    Linköping University

    Advanced-Level Studies in Artificial Intelligence: Natural Language Processing

    Advanced-level studies covering Natural Language Processing, transformer architectures, domain adaptation, sentiment classification and PyTorch-based model implementation, with emphasis on adapting transformer models to domain-specific tasks using Parameter-Efficient Fine-Tuning (PEFT) and Low-Rank Adaptation (LoRA).

    • Natural Language Processing
    • Transformers
    • Domain Adaptation
    • PEFT / LoRA
    • Generative AI / Language Models

    Product relevance

    Strengthened the ability to evaluate how modern language models can be adapted to domain-specific problems and how model capabilities, limitations and technical feasibility affect product decisions.

    Jan 2026 – Jun 2026

    Umeå University

    Advanced-Level Studies in Artificial Intelligence: Autonomous Systems & Perception

    Advanced-level studies in autonomous systems and machine perception, covering multi-sensor fusion, 3D perception, Bird's-Eye View representations, LiDAR point-cloud processing, object detection, trajectory and motion forecasting, path planning and reinforcement learning for adaptive control.

    Explored how perception, prediction, planning and control are integrated to enable data-driven intelligent systems to interpret dynamic environments and support real-time decision-making.

    • Multi-Sensor Fusion
    • 3D Perception
    • LiDAR
    • Prediction
    • Planning
    • Reinforcement Learning

    Product relevance

    Built system-level understanding of AI around uncertainty, data quality, sensor limitations, real-time decisions and safety.

    Completed Nov 2025

    Mälardalen University

    Predictive Data Analytics

    Second cycle

    • Predictive Analytics
    • Machine Learning
    • Prediction
    • Decision Support

    Completed Dec 2025

    Mälardalen University

    Deep Learning for Industrial Imaging

    Second cycle

    • Deep Learning
    • Computer Vision
    • Industrial Imaging
    • Industrial AI

    Bridge · Aug 2025 – Jan 2026 · Innovation Management

    Aug 2025 – Jan 2026

    University of Skövde

    Advanced-Level Studies in Innovation Management

    Focused on strategic innovation, applied innovation processes, implementation and innovation leadership. Studied in parallel with the advanced AI foundation, forming the innovation and product bridge developed further at Blekinge Institute of Technology.

    Talking SCADA — Concept Origin: developed the initial concept for Talking SCADA, exploring how AI and existing operational data from building systems could transform complex system information into understandable insights and decision support for facility managers and operators. The work established the innovation opportunity and concept foundation that was later developed further through Product Management and Requirements work.

    • Strategic Innovation
    • Applied Innovation
    • Implementation
    1. Advanced AI
    2. Innovation Opportunity
    3. Talking SCADA — Initial Concept
    4. Product / Requirements Development

    AI platform / product concept

    Phase 2 · Jan 2026 – Jun 2026 · Product · Industrial Economics · Requirements · Delivery

    Aug 2025 – Jun 2026

    Blekinge Institute of Technology

    Advanced-Level Specialization in Industrial Economics, Product & Requirements Management

    Building on the technical AI and innovation foundation, this specialisation focuses on how customer needs and technology opportunities become viable products, requirements, business models and sustainable value.

    Blekinge Institute of Technology

    Industrial Economics and Management

    • Business Value
    • Technology / Business Perspective
    • Sustainable Value

    Talking SCADA: framed the concept in terms of business value and sustainable value from a combined technology and business perspective.

    Blekinge Institute of Technology

    Strategy and Business Models in Technology-Intensive Businesses

    • Product Strategy
    • Value Proposition
    • Business Model Development
    • Market Relevance
    • Go-to-Market Planning

    Talking SCADA: product strategy, value proposition, business model development, market relevance and go-to-market planning.

    Blekinge Institute of Technology

    Product Management

    • New Product Development
    • Opportunity Identification
    • Product Discovery
    • Product Vision
    • Feature Prioritisation
    • MVP Definition

    Talking SCADA: opportunity identification, product discovery, concept development, product vision, value proposition, feature prioritisation and MVP definition.

    Blekinge Institute of Technology

    Product and Requirements Management for Digital Environments

    • Product Requirements Document
    • System-Level Requirements
    • Functional & Non-Functional Requirements
    • Explainability
    • Reliability
    • Requirements Prioritisation
    • Technical Feasibility

    Talking SCADA: PRD, system-level, functional and non-functional requirements including explainability and reliability, requirements prioritisation and technical feasibility.

    Blekinge Institute of Technology

    Agile Process and Project Management

    • Iterative Concept Refinement
    • MVP Planning
    • Product Development Governance
    • Development Planning
    • Prioritisation / Delivery Thinking

    Talking SCADA: iterative concept refinement, MVP planning, development planning and product development governance.

    Blekinge Institute of Technology

    Leadership in High-Technology and Knowledge-Intensive Organizations

    • Stakeholder Alignment
    • Communication
    • Cross-Functional Perspective

    Talking SCADA: stakeholder alignment, communication and a cross-functional perspective on the concept.

    Continuous product case

    Talking SCADA

    From innovation concept to AI-enabled product case

    Academic Project — Product Management & AI Concept Development · Blekinge Institute of Technology · Aug 2025 – May 2026

    An AI-enabled decision-support concept for SCADA/BMS environments, carried from initial innovation framing through discovery, requirements, MVP definition, product strategy and go-to-market.

    1. Opportunity

      Innovation Opportunity · Initial Concept

    2. AI & feasibility

      Language Interaction · AI Feasibility

    3. Product definition

      Product Discovery · Product Vision · Value Proposition

    4. Requirements

      PRD · Requirements · Prioritisation

    5. MVP & validation

      Conceptual MVP · Validation Approach

    6. Business

      Product Strategy · Business Model · Market Relevance · Go-to-Market

    7. Final

      Technical Feasibility · Adoption Considerations

    • Phase 1 AI studies strengthened the technical understanding behind the language-based interaction and AI feasibility considerations in Talking SCADA.
    • Innovation Management (University of Skövde) contributed the innovation opportunity, problem framing and initial product concept.
    • The Blekinge courses contributed product discovery, requirements, strategy, business model, agile delivery thinking and stakeholder communication.

  7. Now · Direction

    Product & AI Direction

    Bringing together industrial domain expertise, customer understanding, digital-platform experience, technical-commercial judgement, Product Management capabilities and applied AI.

    • AI Product Manager
    • AI Product Owner
    • Offer Manager