But if it filtered it first to "start with the letter R", it would only have to look at perhaps 5% of the results it's trying to verify!

So it's doing needless verification of results that will be thrown out by another filter that should've been applied first!

Since you were part of YC 21, could you share a bit about your pivots/product iterations you went through over the last 4 years?

Congrats on your launch. With the natural way this lends itself to comparison shopping this is an amazing tool for people trying to find "the best X for me" whether that's a TV, a school, etc. So much content that you find on Google when trying to answer that type of query, is designed to trick, bamboozle, and to hide the facts that you might use to answer this question (but most of all to get you to click affiliate links).

Anyway, the model used doesn't seem to be very good, it did not understand a basic "OR" criteria. I asked for a list of companies with an office in Toronto that are involved in hardware development such as custom silicon, robotics, satellites or drones. It completely misunderstood the "or" part (and the "such as" part). E.g. I see many robotics companies marked as a "Miss" because they only do robotics but not any of the other things on my list.

Overall though I love the idea, I would pay for your service (on a pay-as-you-go per-query basis) if the underlying model was smart enough for me to actually rely on the results.

The UI showed literally no change. So I checked and the console shows:

``` Try: 14 Not Found 681-7df1b139fa2dc9f0.js:14:3379 Try: 15 Not Found 681-7df1b139fa2dc9f0.js:14:3379 Try: 16 Not Found 681-7df1b139fa2dc9f0.js:14:3379 Try: 17 Not Found 681-7df1b139fa2dc9f0.js:14:3379 Try: 18 Not Found 681-7df1b139fa2dc9f0.js:14:3379 Try: 19 Not Found 681-7df1b139fa2dc9f0.js:14:3379 Try: 20 Not Found 681-7df1b139fa2dc9f0.js:14:3379 Gave up after 10 seconds. 681-7df1b139fa2dc9f0.js:14:3379 filteredSuggestions Array(3) [ {…}, {…}, {…} ] 681-7df1b139fa2dc9f0.js:14:3379 ```

Also your table doesn't fit in the viewport so I can't see the results.

Firefox Ubuntu.

The initial search/experience is good but then I got dumped here [0] and it's not clear to me if things are still happening or if it broke (it's been at least 5 min with no UI updates.

I can't see the full results yet but this is very interesting and a task I ask OpenAI's Deep Research to attempt periodically. It makes a good show of doing the work but the results are not great IMHO (for asking it generate lists/tables of data like this). I can see this tool being incredibly useful for lead generation (how I am testing it out).

[0] https://cs.joshstrange.com/dySqK1mb

I did one search with 4 criteria, then added the two free columns, and at this point i had spent 750 of my 1000 free credits. The next tier being $49 with only 8000 credits, which means only 10 searches a month.

The search I did was super useful, and I would love to use the product, and reccomend it to my coworkers. But the pricing is what stops me.

Best of luck. I'll probably use it once a month if I can remember :)

1. I love the idea.

2. The UI needs to work on smaller screens (e.g., tablets). The current layout is VERY cramped.

3. Its ability to search for businesses in a given geography is poor. I asked it to search for businesses in a city and it was giving me results that were obviously incorrect from halfway across the country.

4. For a homepage URL for a business, it once gave me a parked domain name at GoDaddy's "domain for sale" page. That seemed like a blunder. Is that because it's pulling in WHOIS information and it connected some addresses?

5. Performance is quite poor. Perhaps that's because you're getting "Hackernews'd" with a surge of people consuming all your capacity.

"robotics servo motors with two-directional control for under $100"

1. https://mjbots.com/ - their motor are $1369. FAIL.

2. https://www.pololu.com/ - this is huge store, but they do have some motors like that. Pass, but wish it linked to specific page and not top top-level one.

3. dh-robotics.com - no prices, but some products on open market are few K$. Likely fail as well.

4. https://www.robotarticulation.com/ - The product is not for sale (early beta), and it looks likely much more than $1K. FAIL.

5. https://www.lynxmotion.com/ - another huge store, most two-directional motors are expensive but there are some under $100... Pass, but wish it linked to specific page and not top top-level one.

I searched for "alternatives to jq with a functional API" and one of the criteria it came up with was "Provides technical details or comparisons relevant to the alternatives" but the table only listed the repo's url and description. And the description was truncated with ellipses with no way for me to resize the columns. Also, it missed the opportunity to tell me that some shells can replicate jq's functionality. Finally, it would have to be faster to be a daily driver. At this speed, it is something I would reserve for backup, for when the workhorse fails. Which means I would not want to pay $49/month.

Hope that helps. Interesting idea.

Our experimental use case is enabling quick and dirty integration of web-based docs into an employee service agentic chatbot - lots of the questions are around “how do I max out my 401k”, which connects to internal information, but some are more like “how do I link a calendar to calendly”.

The one thing I’d love to have in the search product is a cruft cleaner for the results of web queries. Where you have cached the data presumably this wouldn’t add much overhead. Reduces what you have to feed to the LLM downstream and might improve the embeddings performance.

Do you have any built-in features that address these issues?

When I checked this a year or so ago, I might have gotten the impression that it was cheaper. Now, it costs the same as what Perplexity charges for search-grounded queries, which is the same as Google charges for Gemini queries with search.

So basically, one player sets a price, and everyone is anchored on that as the pricing for the entire category? I'm just genuinely interested in why every offering in this space is priced like this.

It seems a bit misaligned with how pure LLM queries are priced.

I have a product that would benefit from search grounding, but this pricing wouldn't work with my volume of queries.

Most of the time I want to find some vendors / companies and Deep Research does that but also responds with a wall of unnecessary text where I just want the table

How do you dedupe entities, like companies and people? I've noticed ChatGPT tends to provide "great" results when asking about different entities, but in reality it just groups similar sounding entities together in its answer.

For example, I asked ChatGPT about a well known startup. It gave me a confident answer about how much they raised, their current status, etc. When looking at the 3 sources they cited though, it was actually 3 different companies that all had similar sounding names that it just grouped together to form its answer.

Basically, how do I trust the output of your system?

I often have projects where the enrichments feature alone would be super useful: I would provide, say, a list of company names, and then use enrichments to qualify them based on location, age, founder experience etc etc.

It disrupts anyone who merely does one thing this does. E.g. contact building app can be done by this. I imagine many "wrapper" apps can be built on this.

I am serious though. It felt like using databricks a little bit, obviously without all the functionality but that will come.

I'm bullish! Modulo competition. Someone who does this makes their billion.

Evals on this would be great to benchmark the gap between using websets versus a generic web search tool. Otherwise to a developer, it's just marketing.

The search engine was impressive enough but I think this implementation was a nice cherry on top.

Very helpful for candidates searching but still a bit slow for every day use Like - “what are the events happening today in my city”

But I believe you guys will crack it soon and make it better

And also how “internal” business intelligence/operations tools should work. search first to find relevant artifacts - “top 10 customers in AMEA”, followed by agentic verification and enrichment.

Congrats on the launch!

Can it perform searches that rely on the rendered (JS-executed) state of the website? If so, does it have access to the DOM?

Example use case: "The 10 most trafficked e-commerce sites that load Adobe Analytics tag(s)."

Normally I'd send this as a DM or email, but I think it could be useful for others to learn about how to use your service/the limitations of it. A couple weeks ago I made a search for:

    In early 2023, Andrej Karpathy said something like "large training runs are a good test of the overall health of the network." Something something resilience as well I think. I need you to find it.

I tried "Full-stack web frameworks started 2023 or later" and the first result was FastHTML which is a very good answer. I was hoping for Dioxus but that I think is actually a little bit older. Of course Google's results, including Gemini, were useless. MeteorJS was not started in 2023 or later. LOL.

some issues I noticed, I searched "lucid air touring models available for sale Under 20,000 miles" and tried to add column "sale price", but did get the price details, same for other cars as well

I think NewsCatcher (my YC startup) and Exa aren’t direct competitors but we definitely share the same insight — SERP is not the right way to let LLM interact with web. Because it’s literally optimized for humans who can open 10 pages at most.

What we found is that LLMs can sift through 10k+ web pages if you pre-extract all the signals out of it.

But we took a bit of a different angle. Even though we have over 1.5 billion of news stories only in our index we don’t have a solution to sift through as your Websets do (saw your impressive GPU cluster :))

So what we do instead is we do bespoke pipelines for our customers (who are mostly large enterprise/F1000). So we fine-tune LLMs on specific information extraction with very high accuracy.

Our insight: for many enterprises the solution should be either a perfect fit or nothing. And that’s where they’re ok to pay 10-100x for the last mile effort.

P.S. Will, loved your comment on a podcast where you said Exa can be used to find a dating partner.

I gave it a try and my first search got one match, 14 misses, and all other results are "Verifying..." but it seems stuck (it's been minutes). I can see why you cut your demo (please don't try to hide that it's so slow, especially since you seem to imply to be a Google competitor ("Google has gotten worse over time"), while your product is incomparably slower than Google; it's more like deep research).