Human in the loop
AI supports decisions. People stay responsible for final outputs.
Why we exist
AI should multiply human capability, not replace it.
Source‑linked outputs
Where possible, outcomes are tied back to documents, sources and review notes.
Privacy aware
Workflows are designed around data sensitivity, access control and auditability.
Founding idea
AI should multiply human capability, not replace it.
Weiser Systems was built from practical medtech and operations experience: capable teams losing time to manual handovers, scattered documents, and knowledge that is hard to reuse.
What matters most is adoption. New tools fail when they force people to learn new processes, new checklists, new vocabulary. So we don't. AI fits into the workflow your team already trusts - not the other way around.
The goal is evolution, not revolution: keep what works, simplify the friction, and replace only what no longer serves the work. When the process stays familiar, adoption happens naturally.
Founder-led consulting practice
Trust & compliance
Built for regulated environments.
Our workflows and internal processes are designed to meet the expectations of life-science vendor qualification.
Data protection
GDPR and Swiss FADP aligned processing. DPAs are available for every engagement.
Human-in-the-loop by procedure
Documented review gates and sign-off before any output reaches regulatory use.
GxP-aware methodology
Workflows are designed with GAMP 5, 21 CFR Part 11 and EU Annex 11 expectations in mind, where relevant to the client workflow. Documentation is prepared to support client CSV/CSA work.
Clinical documentation standards
ICF and patient-facing work is shaped with ICH E6(R3) GCP and EU CTR content expectations in mind, with plain-language principles applied.
EU AI Act readiness
AI-literacy practices are in place for Article 4 awareness. AI-assisted output is disclosed transparently.
Insured & accountable
Professional indemnity insurance, NDAs and quality documentation are available on request. Workflows are advisory tools, not medical devices.
Detailed process documentation and vendor questionnaires answered on request.
Start with one workflow.
A focused 30‑minute exchange is enough to identify whether AI can help, where the risks are, and what a first useful prototype could look like.