Show HN: I've been using AI to analyze every supplement on the market

Show HN: I've been using AI to analyze every supplement on the market pillser.com/...

Hey HN! This has been my project for a few years now. I recently brought it back to life after taking a pause to focus on my studies.

My goal with this project is to separate fluff from science when shopping for supplements. I am doing this in 3 steps:

1.) I index every supplement on the market (extract each ingredient, normalize by quantity)

2.) I index every research paper on supplementation (rank every claim by effect type and effect size)

3.) I link data between supplements and research papers

Earlier last year, I took pause on a project because I've ran into a few issues:

Legal: Shady companies are sending C&Ds letters demanding their products are taken down from the website. It is not something I had the mental capacity to respond to while also going through my studies. Not coincidentally, these are usually brands with big marketing budgets and poor ingredients to price ratio.

Technical: I started this project when the first LLMs came out. I've built extensive internal evals to understand how LLMs are performing. The hallucinations at the time were simply too frequent to passthrough this data to visitors. However, I recently re-ran my evals with Opus 4.5 and was very impressed. I am running out of scenarios that I can think/find where LLMs are bad at interpreting data.

Business: I still haven't figured out how to monetize it or even who the target customer is.

Despite these challenges, I decided to restart my journey.

My mission is to bring transparency (science and price) to the supplement market. My goal is NOT to increase the use of supplements, but rather to help consumers make informed decisions. Often times, supplementation is not necessary or there are natural ways to supplement (that's my focus this quarter – better education about natural supplementation).

Some things that are helping my cause – Bryan Johnson's journey has drawn a lot more attention to healthy supplementation (blueprint). Thanks to Bryan's efforts, I had so many people in recent months reach out to ask about the state of the project – interest I've not had before.

I am excited to restart this journey and to share it with HN. Your comments on how to approach this would be massively appreciated.

Some key areas of the website:

* Example of navigating supplements by ingredient https://pillser.com/search?q=%22Vitamin+D%22&s=jho4espsuc

* Example of research paper analyzed using AI https://pillser.com/research-papers/effect-of-lactobacillus-...

* Example of looking for very specific strains or ingredients https://pillser.com/probiotics/bifidobacterium-bifidum

* Example of navigating research by health-outcomes https://pillser.com/health-outcomes/improved-intestinal-barr...

* Example of product listing https://pillser.com/supplements/pb-8-probiotic-663

This seems more like cataloguing than analyzing

I'd love to see a project that actually analyzes every supplement on the market to make sure it actually contains what it claims to, contains it at the listed dosage, and to show anything else found (heavy metals for example). That's not something AI can do for us though since it'd involve physically collecting and testing samples.

lilouartz · 2 months ago

That's my dream!

That's where I want to take this project.

At the moment, my focus is on what I can do by aggregating and analyzing the available data. Extracting ingredients, normalizing them, normalizing quantities across every supplement, etc. This has already proven to be a lot bigger undertaking than I could have imagined at the beginning of this journey. I had learn a lot about databases, scraping, LLMs, and evals. But it has been a tremendously fun (if sometimes overwhelming) journey.

First, I need to figure out how to monetize what I've built so far. And maybe I cannot, in which case I will start over. But I am trying to find my niche that people uniquely value. So far I found that there are is a pull from people chasing deals (e.g. finding products containing specific ingredients with the highest price per mcg) and people seeking for niche ingredients. This is not exactly the target audience I had in mind when building this, but I am glad they are finding value.

Evolving into performing actual lab tests and producing our own high-quality supplements is my dream.

metalman · 2 months ago

I did something like this, pre LLM, except with food additives.While I dont have the technical expertise to fully evaulate what these substances are, and do, in many cases they are banned in some juristictions, and often have exceptionaly dubious reasons for bieng put in food, I did notice one very stark thing, in that not one single food aditive has ever been held up as " WOW! this stuff is so good!, a boon and benifit, etc, whatever" nothing, zero substances acclaimed as unequivical benifit to humanity. I eat only food now. Oh, and one more thing, many of these things are "white crystaline" substances, which means they are 100% concentrated things that are never found in actual foods, think sugar.

infecto · 2 months ago

Doesn’t that kind of exist already across a couple sites? Thinking consumer labs does this across lots of supplement categories. I have seen a few others too.

lilouartz · 2 months ago

Consumer Labs is definitely the furthest ahead compared to everyone else. I've been using them for many years now.

nebula8804 · 2 months ago

Sounds expensive to test every podunk brand on Amazon. Maybe just the big brands that claim to be accurate like Bryan Johnson's Blueprint.

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Aurornis · 2 months ago

> Technical: I started this project when the first LLMs came out. I've built extensive internal evals to understand how LLMs are performing. The hallucinations at the time were simply too frequent to passthrough this data to visitors. However, I recently re-ran my evals with Opus 4.5 and was very impressed. I am running out of scenarios that I can think/find where LLMs are bad at interpreting data.

It's nice to see an AI-centric Show HN product that uses proper evals and cares about data quality.

How did you build your initial data set that you're using for the evals? Bootstrapping a high quality data set is one of the hardest parts of really knowing how an AI product is performing.

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gavinray · 2 months ago

Unfortunately, none of these data are usable because (in the US, at least) there is no oversight on labeling accuracy for nutritional supplements.

That means I can dump woodchips into capsules and sell them as Multivitamins with 12 vitamins & minerals, and nobody would be the wiser.

There is more rigorous testing being done in underground steroid + peptide communities than in legal nutritional supplements.

Crazy world where you can trust vialed peptides from China more than something you bought on Amazon...

That's true. US is a wild wild west in that regard. However, I am working next to clearly label which supplements have COA vs which are unverified.

NoPicklez · 2 months ago

Sort've related, but here in Australia pet food manufactures are not required to list the nutritional content of their foods, whereas in the US as I understand it they do.

estimator7292 · 2 months ago

They do but the nutritional information guides you to feeding your dog 20,000kcal a day. The suggested serving size on every brand I've seen is about 5 cups for a 70lb dog, whereas my dog gains weight on more than one cup.

At least the "grain free" labels appear to be accurate.

ianburrell · 2 months ago

Supplements should at least be regulated like food. List of ingredients and tests that contains ingredients and doesn't contain anything harmful.

autoexec · 2 months ago

kilna · 2 months ago

Monetize it with Amazon or other affiliate links, and provide dollar per effective dose for a given set of desired supplements.

That's the plan. I don't intend to own any stock. I want to focus on covering the broadest range of supplements across all of the marketplaces, having the richest data about them, and then focus on the affiliate revenue.

The affiliate revenue can be anywhere from 5% to 10% depending on the affiliate partner. Considering no overhead of support, inventory, or logistics, it's a pretty good deal for me, especially for now, while I'm still a solo founder.

krupers · 2 months ago

I just searched the most popular/researched supplement of all time: creatine. There is a mistake in the data there: the Wellnesss Code Whey Protein indeed contains creatine, but not 2g per container, but 2g per serving (that is correctly reflected). Error is easily spotted due to the price per gram being an extreme outlier. That is perhaps something you can look for when evaluating the data gotten from the LLM.

There is interesting context here. The first version of Pillser was focused on very narrow area of supplements, and specifically, supplements sold in the shape of pills (therefore the name "Pillser" [pill search]). However, it kinda snowballed from there, and powder substances were one of the last things I've added. The evals need to be expanded to have more examples specifically around powder substances. However, that's a fix I know how to implement and will prioritize.

Thank you for sharing the example that you've found!

bionhoward · 2 months ago

found a bug searching for "collagen":

I appreciate you letting me know. I can see it in Sentry as well. It's odd though, it looks like it's coming directly from React. There are no traces in my own codebase. I'll try to isolate it.

aiiizzz · 2 months ago

Might be a browser extension fucking with the dom. Just guessing.

pjsg · 2 months ago

I picked Vitamin D as it was an option on the main page. The cheapest offered was $1.1/mg.

Costco (https://www.costco.com/p/-/kirkland-signature-extra-strength...) sells Vitamin D at less than half that price. On Amazon, the two pack of those is even cheaper.

Just an observation.

I think you've mistaken Vitamin D and Vitamin D3

https://pillser.com/search?s=dfbtbc9110&q=%22Vitamin+D3%22

The cheapest price on Pillser for D3 is $0.26/mg

That is odd. When I searched for Vitamin D, it showed me a list (which I could sort by $/mg). That list included Vitamin D, Vitamin D2 and Vitamin D3. I assumed (incorrectly it seems) that this meant that it was doing some sort of prefix match. It seems that the result table highlights the "Ingredient" column, so I assumed (incorrectly) that it was searching that column. However, it doesn't seem to search the "Supplement" column, nor is it doing a prefix match (or substring match) on the Ingredient column. This is just confusing.

https://pillser.com/search?q=%22Vitamin+D%22