Sven Bokn

Founder & CEO

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About

Curious problem solver and product enthusiast with a strong mathematical foundation and expertise in both traditional and cutting-edge AI development. Specializing in building production-grade AI systems with a focus on LLMs and intelligent agents, while maintaining proficiency in traditional machine learning and deep learning techniques. Combines rigorous mathematical thinking with practical implementation skills to solve complex problems. Passionate about information theory and how intelligence creates structured order from chaos. Skilled at delivering end-to-end solutions from concept to production deployment that translate abstract concepts into functional solutions that deliver real business value. Strong background in Python development, cloud architecture, and data science with proven ability to drive innovation.

Services & Expertise

I help organizations build and implement production-ready AI solutions. My services include:

Core Skills

AI & Machine Learning

LLMs RAG Vector Databases Generative AI Computer Vision TTS/STT Technologies NLP Deep Learning ML Algorithms Model Optimization

Development & Cloud

Python Azure AWS GCP REST APIs Data Pipelines Microservices CI/CD Serverless Computing

Data Science

Data Analysis Data Visualization Statistical Modeling Time Series Analysis Big Data Processing A/B Testing

Timeline

2023 - Present
Senaible - Founder & CEO
Founded a Cognitive Research Lab and Startup Studio focused on augmenting human cognition and improving communication between organizations and individuals. Operating as both a product factory that develops practical AI solutions and a research lab exploring the mathematical foundations of consciousness and intelligence.

Developing two flagship products: Omegn (Live) - an AI-powered solution helping institutions communicate effectively with their audiences, and CoWorker (Building) - a pioneering project creating cognitive layers for organizations by synthesizing internal communication and data.
2021 - 2023
Hjemla - Data Scientist
Developed and maintained production-grade machine learning models for Norway's leading automated property valuation system. Built optimized data pipelines in Python for processing large-scale real estate datasets. Implemented AWS-based cloud architecture for ML model deployment and data processing. Created performance-tuned algorithms to predict market values using statistical and machine learning approaches.
2020 - 2021
TietoEVRY, Financial Services - Data Scientist
Developed prototype ML models using TensorFlow, Keras, and Python for financial transaction analysis. Created proof-of-concept solutions for personalized finance and customer behavior insights. Designed risk assessment models for loan applications and implemented cloud-based solutions on Microsoft Azure for financial applications.
2019 - 2020
University of Bergen - Topics in Statistics and Machine Learning
Selected coursework in statistics and machine learning to build practical data science skills. Self-directed study bridging pure mathematics background with applied computational methods. Developed foundation for career shift into AI and data science.
2019
University of Trento - 11th School on Analysis and Geometry in Metric Spaces
Participated in advanced research workshop on geometric measure theory in Carnot-Caratheodory groups. Engaged with cutting-edge concepts in metric spaces with applications to degenerate elliptic equations, optimal control theory, and differential geometry. Collaborated with international researchers on current developments in the field.
2018 - 2019
University of Bergen - Teaching Assistant
Served as teaching assistant for MAT235 - Vector and Tensor Analysis while simultaneously enrolled as a student in this challenging postgraduate course. Prepared teaching materials, held lectures, and evaluated student assignments and midterm exams. Guided fellow students through complex mathematical concepts and problem-solving techniques.
2018
The Fields Institute - Connections Between Complex, Harmonic, and Stochastic Analysis
Selected to participate in international workshop connecting researchers from Norway and Canada. Explored interdisciplinary connections between Stochastic Analysis, Harmonic Analysis, Geometric Function Theory, Mathematical Physics, and Geometry. Developed deeper understanding of cross-disciplinary mathematical applications.
2017 - 2019
University of Bergen - Master's in Pure Mathematics
Completed Master's degree in Pure Mathematics with focus on Mathematical Analysis and Differential Geometry. Developed strong foundation in advanced mathematical concepts including functional analysis, differential geometry, and measure theory.

Final thesis received grade A.
2017
UC Berkeley - Topics in Pure Mathematics
Exchange program studying Number Theory, Differential Geometry, and Fourier Analysis (Signal Processing). Gained international academic perspective at a world-leading institution.
2014 - 2017
University of Bergen - Bachelor's in Mathematics
Completed Bachelor's degree in Mathematics with comprehensive foundation in mathematical principles and theories. Developed skills in scientific writing and mathematical analysis. Coursework included complex analysis, real analysis, algebra, and linear algebra.

Final thesis received grade A.

Highlighted Projects

2023 - Present

Omegn - AI-powered Cultural Communication Solution

Client: Senaible (In-house product development)
Project role: Project Management | Product Development | AI Architect

Project goal and description
Development of "Omegn," an innovative AI-powered solution for cultural communication and heritage accessibility. The system delivers personalized and engaging experiences to visitors at cultural institutions via smartphones, without requiring app installation. The goal is to enhance communication and increase engagement among diverse audiences.

Sven's role and responsibility
Sven designed and developed the AI architecture, including the integration of Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems for contextual information retrieval. He built core Natural Language Understanding (NLU) modules, implemented vector databases for efficient knowledge retrieval, and set up a scalable cloud infrastructure on Microsoft Azure. His responsibilities cover the full product development lifecycle, from concept to production, including business development, technology selection, and implementation of solutions for data ingestion, Text-to-Speech (TTS), and Speech-to-Text (STT). The solution was developed in close collaboration with cultural institutions to ensure market fit and address real user needs.

Competencies
Python, Microsoft Azure, LLM, RAG Architecture, LangChain, Vector Databases, API Development, Prompt Engineering, NLU, TTS/STT, Computer Vision, Data Pipelines, SaaS, Product Management, Business Development, Client Collaboration.

2021 - 2023

Automated Property Valuation System

Client: Hjemla
Project role: Data Scientist

Project goal and description
Development and maintenance of Norway's leading automated property valuation system. The system provides accurate and real-time property value estimates, utilizing large-scale real estate data and advanced machine learning models to support data-driven decisions in the property market.

Sven's role and responsibility
Sven was responsible for developing and maintaining production-grade machine learning models for the core valuation engine. This included building and optimizing data pipelines in Python for processing and analyzing extensive real estate datasets on AWS. He designed and developed APIs for data access and integration, created performance-tuned algorithms using statistical and machine learning techniques, and implemented MLOps practices for continuous model improvement and deployment. His work involved extracting insights from property market data using big data analytics.

Competencies
Python, AWS (Amazon Web Services), Machine Learning, Statistical Modeling, Data Pipelines, API Development, MLOps, Big Data Analytics, Data Analysis.

2020 - 2021

AI-driven Personal Finance Management (PFM) PoC

Client: TietoEVRY, Financial Services (Internal PoC for banking clients)
Project role: Data Scientist & AI Advisor

Project goal and description
Development of a Proof of Concept (PoC) for an AI-driven Personal Finance Management (PFM) solution, designed to demonstrate the value of automated transaction categorization for enhancing digital banking services. The goal was to showcase how AI could provide bank customers with better insights into their spending patterns.

Sven's role and responsibility
Sven led the data science and machine learning development for the PFM PoC. He analyzed large volumes of anonymized transaction data to identify spending patterns and built machine learning models (using TensorFlow/Keras) for automated transaction categorization, running simulations locally to demonstrate functionality. Sven also acted as an AI advisor, participating in client meetings with banks to present the PoC, explain the AI capabilities, and discuss potential integrations into their online and mobile banking platforms. He contributed to conceptualizing front-end solutions like microfrontends.

Competencies
Python, TensorFlow, Keras, Machine Learning (Classification), Data Analysis (Financial Transactions), Prototyping, PoC Development, AI Advisory, Client Presentations, PFM Concepts.

Media

Sven Bokn's Message to Young Dreamers

Don't be afraid to fail. Discover how Sven Bokn's unconventional career path led him to found Senaible and develop Omegn - the future of cultural communication. Read his inspiring advice about following your dreams and embracing life's detours


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Mathematics: The Language of Nature

Explore how Sven Bokn uncovers mathematical truths with the precision of a detective, finding beauty where others see only numbers. Learn why he embraces the "99% hopelessness" that leads to undeniable proofs and why mathematics teaches you to solve any problem life presents.


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