Comment by Xandr-AJ

Comment by Xandr-AJ

Hi HN, I’m John, the builder. Tabibu (“doctor” in Swahili) is a health-information service for Kenya. I started it because general chatbots give the same answer in Nairobi as in New York: they don’t know that SHA replaced NHIF in 2024, that a fever in western Kenya should raise malaria, that “Brufen” is ibuprofen, or that 999/112/1199 are the numbers that matter, not a US crisis line.

What it does: it answers questions in English or Kiswahili from a library of Kenyan Ministry of Health guidelines, the Essential Medicines List, SHA material and Kenyan law, and shows the numbered sources it used. There’s also a free SHA/SHIF contribution calculator checked against sha.go.ke (2.75% of income, KSh 300 minimum). You can ask without an account.

How it’s built: retrieval over the guideline library, then an LLM writes the answer (question text goes to OpenAI; the privacy page lists every processor). Emergency escalation is rule-based and runs before the model. I keep a test set of 261 emergency and non-emergency phrasings (English, Kiswahili, Sheng and four other languages): a message describing a stroke or self-harm should get the Kenyan emergency card first, and a research question that merely mentions “stroke” should not. Adding the 2026 guidelines moved the share of expected facts found in the top 5 retrieved passages from 44% to 72% on 41 questions I wrote. These are my own test sets, not clinical trials.

What it isn’t: it doesn’t diagnose and it isn’t clinically validated or certified. Prescription, child and high-risk doses are meant to be deferred to a clinician, but that is a rule that reduces risk, not a guarantee: today I found and fixed a case where it quoted formulary doses, and I now have regression tests for it. Kiswahili has only been reviewed by AI so far; a native-speaker review and a clinician review are still pending. On a HealthBench subset I ran (same grader, not leaderboard-comparable), the Tabibu pipeline scored below the bare underlying model, so I’m not claiming it is a better general doctor, only that it knows Kenya and shows its work.

Free: 25 questions a day. Paid: KSh 500 / 1,500 a month. Norah Labs is ODPC-registered in Kenya. I’d most like feedback on the safety rules, the source-citation UX, and wrong or outdated SHA facts (every page has a “tell us” link). Happy to go deep on the retrieval and safety design.

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