AI case analysis — the simillimum from your own cured cases

Faster, more confident prescribing — with an AI that learns from the cases you actually cure.

The problem

Repertorising and then confirming the simillimum across a busy OPD is slow, and static "expert systems" never learn from whether your patients actually got better. The clinical signal in your own results is lost.

How it works

Suggests the simillimum from the case

From the patient’s symptoms, generals and constitution, the engine surfaces the most likely remedies — as a starting shortlist you confirm, not a black box.

Searches your own cured cases

It finds similar patients from your clinic’s history whose cases were cured, so you can see what worked for a patient like this one before.

Predicts likely cure time

From past outcomes for similar cases, it estimates how long recovery typically took — useful for setting patient expectations.

Whole-patient constitutional matching

It matches on thermal, thirst and mind/emotional state — the whole person — not just the complaint text, which is central to choosing the simillimum.

Why it’s different

Generic clinic software has no homeopathic intelligence at all, and repertory/expert-system tools are static — they don’t learn from your results. HomeoAxis improves as you practise, because it learns from your clinic’s own cured cases.

Frequently asked questions

Does the AI replace the homeopath?

No — it’s decision support. It surfaces a shortlist and similar past cases; you make the prescription. It speeds up case analysis and adds confidence, it doesn’t prescribe for you.

Where does the AI learn from?

From your clinic’s own anonymised, cured cases (with privacy controls), so suggestions reflect what actually works in your practice.

Is patient data private?

Yes — the learning uses anonymised case patterns with org-level controls, and you decide whether to contribute to or read from a shared pool.

Run your homeopathy clinic on HomeoAxis

Practice management + clinical intelligence + patient growth, in one platform.

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