simili.ai is the first homeopathic remedy finder that combines three independent methods — statistical evidence, pattern recognition, and AI clinical reasoning. Validated on hundreds of blind-tested cases. Describe your symptoms in plain language — in any language — and simili.ai matches them against classical repertory sources.
“Similia similibus curentur”— Samuel Hahnemann, Organon der Heilkunst, 1796
Four steps from symptoms to simillimum. In any language you speak.
Tell simili.ai about your symptoms in plain language. English, Dutch, French, German, Spanish — describe what you feel in whatever language comes naturally.
simili.ai asks targeted follow-up questions to narrow down the differential. “Is the patient worse on the left side?” Each answer shifts the ranking.
Three independent engines rank the most likely remedies. When all three converge, confidence is highest. Results show probability scores and engine agreement.
Dive into biochemical profiles, mechanism of action, and clinical signs for each suggested remedy. See where historical observations meet modern pharmacology.
Each method catches cases the others miss. Together, they cover each other's blind spots.
Hundreds of thousands of symptom-remedy likelihood ratios drawn from classical repertory sources and validated clinical cases. Each symptom shifts the probability — pure statistical inference, no guesswork.
Statistical evidenceRecognises the overall disease picture — the way an experienced homeopath recognises “this looks like a Lachesis case.” Catches rare remedies that symptom-by-symptom analysis would miss.
Pattern recognitionAn AI reads the full patient presentation and generates clinically relevant descriptions — understanding that “worse from heat” also implies “desire for open air” and “restless in warm rooms.” Like a homeopath thinks.
Clinical reasoningA real Lachesis case — watch simili.ai work through it step by step.
Seven layers of technology that turn your words into evidence-based remedy suggestions.
19th-century English symptom texts are translated into modern clinical language, making them searchable and comparable. "Stitching pain in the praecordial region" becomes "sharp chest pain in the heart area."
Semantic embeddings map every symptom into a mathematical space where meaning matters, not spelling. This is why simili.ai understands any language and matches concepts, not just keywords. "Hoofdpijn" (Dutch), "Kopfschmerzen" (German), and "headache" all land in the same region.
An LLM reads your natural-language description and identifies specific symptoms, mapping them to the correct classical rubrics from Kent, Hering, Boericke, Allen, and Lippe. One sentence can contain multiple symptoms — the AI finds them all.
Three independent methods score every remedy. The Bayesian Evidence Engine uses hundreds of thousands of likelihood ratios from classical repertory sources for pure statistical inference — the same math your doctor uses. The Concept Pattern Matcher compares the patient's overall disease picture against each remedy's characteristic pattern — the way an experienced homeopath recognises “this is a Lachesis case.” The AI Clinical Reasoning engine generates and validates clinical descriptions the way a homeopath would during case-taking. Each method catches cases the others miss.
Each remedy receives a confidence rating based on how many engines independently converge on it. ★★★ means all three methods agree — the highest confidence. ★★ means two methods agree. ★ means one method suggests it. This gives practitioners a clear signal of diagnostic certainty — and tells you exactly how much weight to give each suggestion.
We extracted the chemical compounds of remedy source substances and compared them against SIDER, a database of 163,000+ known pharmaceutical side-effects. For key remedies like Arsenicum album and Belladonna, the majority of known pharmaceutical effects were already described in 19th-century provings. This suggests that historical observers captured real, measurable pharmacological phenomena.
There is measurable overlap between homeopathic remedy indications and conditions treated by conventional pharmaceuticals. simili.ai surfaces this overlap — not to create conflict, but to assist integrative practitioners who work with both traditions. Same data, different lens.
We compared classical remedy descriptions against SIDER, a database of 163,000+ pharmaceutical side-effects. The data shows notable patterns.
The SIDER comparison above illustrates individual cases. In a systematic study across 78 remedies, we used embedding-based semantic alignment to compare 19th-century proving symptoms against modern clinical toxicology. Result: 22 remedies show statistically significant alignment (22.6× enrichment, p = 9.8 × 10⁻²⁴), while negative controls (lactose, ethanol, mineral water) show no signal. This suggests that where a substance has known toxic effects, historical provers independently described them.
All data on this page is extracted from our database — SIDER pharmaceutical side-effects, classical repertory sources, and the ATC drug classification system. Nothing is invented or generated. This demonstrates internal coherence between historical observations and modern pharmacology. It does not constitute evidence of homeopathic therapeutic efficacy.
Whether you practice homeopathy, integrative medicine, or conventional medicine — simili.ai provides data-driven insights into 200 years of clinical observations.
Bayesian likelihood ratios, pattern matching, and AI reasoning — three methods, all grounded in evidence-based principles.
SIDER pharmaceutical side-effects, ATC drug classifications — the same data used in drug safety research.
Classical homeopathic observations viewed through the tools of modern data science. No conflict — just data.
You can. But here's what happens behind the scenes — and why the answers are fundamentally different.
A language model predicts the next most likely word. When you ask about a remedy, it retrieves whichever remedy appeared most often near those words in training data — a popularity contest, not a medical calculation.
simili.ai matches your symptoms against a curated database of graded symptoms from classical sources. Three independent engines each score every remedy, and the results are combined using a confidence system. Every score is traceable — you can see exactly which symptoms drove each ranking.
Water, quantum biology, and the science we find fascinating.
22 of 78 remedies show statistically significant semantic alignment with modern clinical toxicology (22.6× enrichment). Negative controls show no signal.
Could water be a quantum computer? An exploration of quantum biology, graphene structures, and coherent water.
Water defies known physical laws. A look at what we do and don't understand about the most common molecule on Earth.
At supercooled temperatures, water exists as two distinct liquids with different topological structures. Published in Nature Physics.
Protons in water trimers bypass energy barriers through coordinated quantum tunneling. Published in Nano Letters.
Each water molecule forms one strong and one weak hydrogen bond, creating organized structures that contradict assumptions about liquid disorder.