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Jacques Buis
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Applied AI engineer · Copenhagen

Jacques Buis

AI systems engineered end to end — from retrieval and model orchestration to evaluation and the data beneath them — secure by design and measured against real data.

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Practice

Systems that have to hold up in production, not in a demo.

Permission-aware RAG, multilingual event resolution and LLM-based system design, built for clients in Aarhus and Copenhagen, mostly on open-weight models, so client data never reaches a third-party model provider.

  1. 01

    Retrieval

    Hybrid BM25 and dense retrieval with cross-encoder reranking. Answers cite their sources or refuse.

  2. 02

    Orchestration

    LLM-based system design and model integration, built on open-weight models.

  3. 03

    Data systems

    Stateless, horizontally scaled services provisioned through reviewed infrastructure code; evaluation on human-labelled production data.

Selected work

01 · Systems and constraints

Permission-aware document assistant

Related, Aarhus · AI consultant · 2025 –

A Danish/English AI assistant that answers only from the documents each employee is allowed to see.

Role
Sole engineer, end to end: retrieval, access control, LLM answers, evaluation and interface.
Outcome
Zero permission leaks in full access-control testing. Answers cite their sources or decline, 95% within two seconds.
Stack
Python · RAG · hybrid search with reranking · self-hosted open-weight LLM

02 · Comparison and evidence

Multilingual event resolution

Riskline, Copenhagen · AI consultant · 2025–2026

Detecting when notifications from different sources and languages report the same real-world event, designed so that no merge is ever hidden from human review.

Role
Designed and built the prototype resolution pipeline and evaluated it on real notification data.
Refinement
Refined the approach toward production. Planned a human-labelled evaluation with measured labeller agreement, a simple baseline first, and a frozen held-out test set scored per language and per source.
Delivered
The working prototype, plus a staged plan for a scalable production service on AWS, including a repeatable load test.

03 · Adaptation and discovery

AI product development for e-commerce

CustomerSense, Copenhagen · AI architect · 2025 –

An AI system for an e-commerce consultancy, currently in development.

Role
AI architect and engineer, responsible for the AI layer and technical architecture.
Approach
LLM-based system design, open-weight models and model integration.
Status
Working proof of concept; development ongoing.

04 · Independent work

Questions of my own

Questions I have followed on my own, beyond commissioned work: research, competitions and study, each carried from a first idea to a considered answer.

Each project closes with its own materials (papers, code and notebooks) to download or open, for anyone who wishes to explore it in greater depth.

About

The discipline behind the work.

Jacques Buis is an applied AI engineer in Copenhagen. Since July 2025 he has run his own consultancy, Buis AI & Data Science, building retrieval, model orchestration and data systems for client teams in Denmark.

Four principles the work demonstrates

  1. 01

    Permissions belong inside retrieval.

    One access row per document: a missing row means deny, and sources that cannot resolve their permissions are quarantined, never filtered after the fact.

  2. 02

    Stop at the cheapest stage that can settle a case.

    Identity checks first, then a learned pairwise model over a bounded window, then human review of every proposed merge, kept with its evidence.

  3. 03

    Keep client data out of third-party models.

    Open-weights models run on rented GPUs, so no client data is ever sent to an outside model provider.

  4. 04

    Measure what an approximation costs.

    Evaluation on human-labelled real data with a frozen held-out test set. The bachelor thesis, awarded the highest possible grade, measured how losses in approximate similarity search travel into downstream tasks.

Experience

  • 2025 –
    Founder and AI engineer, Buis AI & Data ScienceHis own AI consultancy, based in Copenhagen.
  • 2025 –
    AI consultant, Related (Aarhus)A Danish/English document assistant that answers only from what each employee may see, and cites its sources.
  • 2025 –
    AI architect, CustomerSense (Copenhagen)An AI system for an e-commerce UX consultancy, designed end to end.
  • 2025 – 2026
    AI consultant, Riskline (Copenhagen)Event resolution for a multilingual risk-notification stream, evaluated per language and per source.
  • 2024 – 2025
    AI analyst, Human Risks (Aalborg)Automation with Selenium and AI-assisted scrapers for criminological OSINT.
  • 2023 – 2025
    Data scientist, freelancePython data science for academic and research projects.
  • 2023 – 2025
    Front-end developer, freelanceUX-focused web projects in HTML, CSS, JavaScript and MySQL.
  • 2021 – 2023
    Mathematics tutor, Nyborg GymnasiumUpper-secondary mathematics, pairing theory with demonstrations in programming tools.

Education

  • 2023 – 2026
    BSc Artificial Intelligence, University of Southern DenmarkGraduated with the American equivalent of magna cum laude, with one of the highest GPAs in the programme cohort; bachelor thesis awarded the highest possible grade.
  • 2021 – 2023
    International Baccalaureate, Nyborg GymnasiumAmong the top 10 % of IB scores worldwide; CAS Achievement Award for outstanding service.

Languages and certificates

  • Languages
    Danish, Russian and English, all at native level
  • Certificates
    Machine Learning Scientist with Python · Data Scientist Professional with PythonDataCamp

Contact

Let's talk.

For AI engineering of any kind, from an early idea to a system in production, or simply to talk through any of the work above.

Copenhagen, Denmark

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