Truth, grounded. Intelligence, verified.
AI that shows its work
vinTsys builds AI systems that cite their sources, verify their results, and earn the trust of researchers and institutions.
See it in action with ScholarInt and our Learning Hub.
ScholarInt — an AI learning assistant that grounds every answer in your institution's own material.
Learning Hub — the technical journal, written from the inside.
ScholarInt — AI Learning Infrastructure for Institutions
ScholarInt is a guided learning platform that provides an intelligent layer for academic workshops and courses. It pairs a structured, stage-based curriculum with a Q&A assistant grounded in your workshop's own course material — so every answer is source-backed, with traceable citations, as you work through the content.
Planned to be deployed in bioinformatics and computational life sciences education, ScholarInt runs on workshop materials from the BioNT European training network. The platform is designed to extend to any domain where reproducible, citation-backed learning matters.
- Grounded answers, not guesses — every question you ask is answered by retrieving relevant passages from the workshop's course material (slides, papers, documentation) and generating a response from those passages, with sources cited.
- Stage-based curriculum — content is organized into sequential stages, each with its own learning objectives, topics, and a short quiz to confirm understanding before you advance.
- Progress that's tracked for you — your stage progress and quiz attempts are saved to your account, so you can pick up where you left off.
- GDPR-compliant by design — data stays within a private cloud environment
ScholarInt is in the initial planning stages.
LLM Architecture & Agentic Systems — Learning Hub
vinTsys - learn, a public learning journal documents the internals of large language models and agentic systems — from tokenisation and attention mechanisms to context engineering and trust. Written from the perspective of a genomics researcher who built these systems from the ground up, not from the outside in.
Read at learn.vintsys.com →Building Blocks of GPT-2
tokenisation, embeddings, attention, transformer architecture
Architecting Autonomous Systems
agent anatomy, MCP, context engineering, and engineering trust
AI Agent Tutorials using Google ADK
building agents with Gemini 3.1 Pro, BigQuery & Google Maps via MCP, context engineering, context caching & compaction, and persistent memory with GoodMem
Recognized in BioNT's Sustainability Plan
BioNT is an EU-funded consortium developing open training resources in bioinformatics and computational life sciences. ScholarInt is built as an intelligent layer on top of these openly available materials, providing the structured learning experience, adaptive assistance, and assessment infrastructure that institutions need to deploy them at scale.
vinTsys's work is documented in two of BioNT's official deliverables to the European Commission: the project's Third Year Impact Assessment, which records vinTsys as an example of the potential use of consortium's materials, and BioNT's Sustainability Plan, where vinTsys — registered as a Norwegian spin-off — is cited as a case of how BioNT's training resources can be reused beyond the project's timeline.
In effect, an EU consortium's own reporting to the European Commission holds up vinTsys as evidence that its work outlives the project.
Built because the problem was too important to ignore
AI is reshaping research and education. However, current generic AI tools share a fatal flaw: they produce answers with citations that cannot be verified against your own domain-specific materials and operate on generic knowledge rather than the specialised content your work actually depends on. This can leave institutions with no way to audit what they're getting. In high-stakes research and education, that is not a gap — it is a liability.
The mission of vinTsys is to build AI systems grounded in your domain's own content. We aren't here to ride the AI wave; we are here to build traceable, verifiable systems that institutions can actually trust.
vinTsys was founded to explore AI in education and professional training — researching frameworks designed for institutional trust. That focus is deliberate: education is where trust in AI is most visibly broken and where the impact of getting it right is immediate. The same foundations that make this possible — domain-grounded content, traceable and verifiable outputs — extend naturally into active research. Our long-term vision aims in that direction: exploring how to give research teams customisable, verifiable AI that operates on their own materials, in their own domain, on their own terms.
Interested in vinTsys?
Currently we do not offer commercial services or products
(currently a dormant entity).
Write to us: hello@vintsys.com