We develop next-generation clinical intelligence tools combining artificial intelligence, SNOMED CT terminology, and cloud infrastructure — designed for real-world healthcare, scalability, and accessibility from the ground up.
Mission
Arachnet aims to transform how medical knowledge is represented, processed, and applied in clinical practice — enabling structured, interoperable, and accessible reasoning systems at scale. Accessibility is not an afterthought here. It is built into the core architecture, developed in part by a blind engineer.
Domain-aware embeddings and semantic processing built on SNOMED CT international terminology standard, enabling advanced clinical reasoning support.
Inclusivity is core architecture, not an add-on. Tools designed to work for visually impaired practitioners and patients from the very first line of code.
Semantic interoperability across systems, enabling efficient querying of complex medical data and integration with AI and machine learning pipelines.
Architecture separated into ingestion, validation, and inference layers, ensuring robustness, auditability, and compliance from the beginning.
Projects
Two interconnected systems forming a long-term platform vision for clinical AI.
A domain-aware clinical embedding platform built on SNOMED CT, designed to transform complex medical terminology into machine-understandable representations using a custom, clinically structured approach.
An AI-assisted diagnostic tool for physiotherapists focused on musculoskeletal conditions, with accessibility as a primary requirement. Supports symptom-based reasoning and enables visually impaired practitioners to perform structured diagnostic workflows.
Technology
Built on a modern, scalable stack designed for clinical-grade reliability, hosted on Oracle Cloud Infrastructure in Frankfurt.
Roadmap
A phased approach that reduces risk while enabling early validation and iterative improvement.
Collaborate
Arachnet is actively seeking strategic partners across healthcare, research, and technology.
Rehabilitation centers, physiotherapy and musculoskeletal specialists, and clinical organizations interested in AI-assisted workflows.
Universities, public health organizations, and AI and data science collaborators working at the intersection of clinical terminology and machine learning.
Assistive technology specialists and accessibility advocates who share our commitment to inclusive clinical tool design.
Support
Arachnet Project z.s. operates as a Czech non-profit initiative focused on high-impact innovation in healthcare. Early support enables acceleration of development, clinical validation, and scaling into broader healthcare markets.
Your contribution directly funds development of clinical AI tools designed to be accessible to everyone — including visually impaired professionals and patients. All support is received by Arachnet Project z.s., a registered Czech non-profit.
For partnership and investment enquiries:
Contact
Whether you are a potential partner, collaborator, researcher, or supporter — we would like to hear from you.
Email: arachnet@maserna.org
Web: arachnet.eu
GitHub: github.com/arachnet
Licensed under Business Source License 1.1 · SNOMED CT used under official affiliate license · Arachnet Project z.s. · Czech Republic