Our AI is judged on what it refuses to say.
Assiz builds software for clinical documentation, pharmaceutical research, child sponsorship and regulated health marketing. In all four, a confident wrong answer does more damage than no answer at all. So we build the limits first and the features after.
Four of them, in four countries
Each one started as a specific, unglamorous problem somebody was already losing hours to every week.
Clinical Smart Scribe
Clinical documentation with a facts-first pipeline. It pulls out what was actually said, then drafts from that alone, so it can't quietly fill a gap with something plausible. SOAP, narrative or ED format. A clinician signs off every one.
Visit product ↗REGENOVA-Intel
A prescribing assistant for peptide therapy that ranks its own sources. Answers come back with a safety check, an evidence tier and a citation attached. In testing with a Canadian client.
Visit product ↗Cardiology Companion
Cardiology residents interview an AI standardised patient out loud, then get a debrief flagged green, orange or red. The AI plays the patient and never the doctor. Built with AL-I in California.
Case studyHop
A sponsor portal for an orphanage in Tanzania. Sponsors eight thousand kilometres away can see that the thing they fund is still going. Staff schedule a term of updates once instead of writing them one at a time.
Read the case studyThe limit is the product
Clinical notes. Prescribing decisions. Children's records. Regulated health advertising. Medical training. Across all of it, the useful part isn't what the model can say. It's what we've stopped it from saying.
Every build has a refusal in it
The scribe extracts stated facts before it drafts, so it can't invent clinical detail. REGENOVA weights every source across five evidence tiers. Tecmaze health sites follow AHPRA advertising rules from the first line. The Builders Lab collects nothing at all.
Someone qualified signs off
Clinicians review every note and every prescribing answer before it counts. Trainees get a debrief, never a grade from a black box. No system we've built makes a call that belongs to a professional.
Built to be audited
Data minimisation, authenticated access, retention policies, handover documentation. All of it written for whoever has to answer for the system later. Usually that's the client rather than us.
From a problem you described to a system you run yourself
Discover
We start inside your workflow. Most engagements open with us watching the process the AI is meant to take over, before anybody writes code.
Build
Proxied API access, role-based control and audit trails go in during the first sprint. They're painful to retrofit and cheap to build in early.
Deploy & Operate
You get something your own team can operate, documented for someone who doesn't code. We stay on while the organisation changes around it.
Clients and partners in six countries
Canada, Tanzania, the United States, Australia, India and the UK.
Something in your organisation is slow, manual and error-prone.
Tell us which thing. If AI is the wrong tool for it, we'll say so and you'll have lost an email.