The second half of Y Combinator’s Winter 2024 cohort presented on Thursday, once again bringing dozens and dozens of new startups before a chunk of the venture investing community. As we did on Wednesday, a number of the TechCrunch crew watched the entire run of presentations, picking out a handful of favorites to highlight.
Enjoy our favorites from the second round of Y Combintor demos while we go out and buy another few pots of coffee. To work!
TechCrunch’s staff favorites
Atopile
What it does: Lets electrical engineers design circuit boards using code
Why it’s a fave: Lots of electrical engineering work on circuit boards is done via GUIs. Who knew? Not this writer, which is why Atopile piqued my interest immediately. The startup, co-founded by Matt Wildoer, Timothée Peter and Narayan Powderly, aims to bring design reuse, version control and automation to hardware design — aspects that the trio claims are seriously lacking in existing design tools. Instead of forcing electrical engineers to draw schematics by hand and validate every small change on test benches, Atopile captures a product’s requirements using a custom programming language and, from there, builds and validates the necessary manufacturing files. Nifty.
Who picked: Kyle
Scritch
What it does: A platform for vets to run their practices
Why it’s a fave: So, platforms to run vet businesses aren’t new, as I’ve discovered after a cursory Google search (or a few). BUT, Scritch’s co-founders – Claire Lee and Rachel Lee – say that what makes theirs different is a heavy reliance on automation. Scritch handles scheduling, billing and clinical workflows as well as inventory management and care coordination. In addition, the platform supports vet customers by filing insurance claims on their behalf – which sounds like a very attractive feature for this would-be pet owner.
Who picked: Kyle
Lantern
What it does: Postgres vector search tool
Why it’s a fave: If you cover the AI world at all, you’ve heard of vectors. There are companies like Semi that have raised lots of capital for their own open-source vector database software, for example. Lantern sells a hosted Postgres vector database on its own Lantern Cloud. Its pitch: their product is cheaper than a similar offering from AWS. Continuing my hunt for the startups that might make lots of picks-and-shovels money from the AI boom, I’m adding Lantern to the list.
Who picked it: Alex
Paradigm
What it does: AI agents for task automation
Why it’s a fave: There’s been lots of talk about using AI to replace workers who execute repetitive tasks. More interesting in the near-term are AI tools that help those same workers do more, faster. That’s what Paradigm is building for the marketing and sales market use cases, with a human-in-the-loop angle. I’ve spent enough time with business development representatives and account executives to know that the market for this tech could be huge.
Who picked it: Alex
Just words
What it does: GenAI to help companies write better
Why it’s a fave: When Just Words founder Neha Mittal worked at Twitter and Pinterest she discovered that minor word changes in user-facing communications had a big impact on engagement rates. That tracks with what I’ve learned writing online. The startup’s plan to bring a similar sort of boost to customers may prove popular; I chose it as a favorite because it fits neatly into a theme I have noticed since the rise of ChatGPT and similar services: people hate writing. They don’t want to do it! So, tools that help people not write are going to be big.
Who picked it: Alex
Pythagora
What it does: Builds apps and refines them from text prompts
Why it’s a fave: I love two things about this. First, it has $47,000 worth of monthly recurring revenue — $564,000 ARR — from 140 customers in less than a quarter. That’s a lot, quickly. And second because of the way that it describes an interactive approach to app development, in which you answer questions and then it codes up what you have in mind. I am downloading Visual Studio to give this a try, but the concept itself is very appealing to me, someone who has not really written code since high school. (Later in the day, Marblism shared a related pitch that I would be remiss to not include here.)
Who picked it: Alex
CommodityAI
What it does: AI-power shipment management for commodities trading
Why it’s a fave: Trading commodities involves cross-border communication, strict adherence to import laws and a lot of paperwork. CommodityAI’s mission — to bring all the invoices and paperwork involved in commodities trading online and add a collaboration layer on top of it — makes a lot of sense. This seems like a big improvement over parties having to call each other in other countries to double check numbers and data on paper documents — if they can find them.
Who picked: Becca
Kopia
What it does: Partners with apparel retailers to allow shoppers to try on clothes virtually
Why it’s a fave: I don’t love buying clothes online because it’s hard to predict what items will look like on my body, and sending packages back is a pain. Kopia wants to help consumers visualize how outfits will fit by dressing an avatar that mimics the person’s body type. Other startups have tried the idea of a virtual fitting room, but I still haven’t seen these tools available on shopping sites. Will Kopia’s product pique retailers’ interest? Hard to say, but I hope that they or another company figures this out because I sure need a wardrobe update.
Who picked: Marina
Care Weather
What it does: More accurate weather data using low-cost flat satellites
Why it’s a fave: Getting weather forecasts correct is incredibly important because inclement weather can affect people, structures and supply chains. I really like that this company is not only trying to make weather forecasts more accurate, but that it’s doing so by building less-expensive satellites. The company says its tech is 17x more accurate for predicting weather outcomes than existing systems — a lofty statement. Even if it’s not as accurate as the startup claims, I’m a fan of anything that will better help me predict when my building’s basement is going to flood.
Who picked: Becca
Miden
What it does: infrastructure for card issuer processing and core banking for businesses in Sub-Saharan Africa
Why it’s a fave: Technology for Sub-Saharan Africa is not something you hear of often in startup land; tech for B2B companies located in that region is even less common. Building fintech infrastructure so that companies can issue cards, or even just file expense reports, seems like a smart foundation for the company to get customers and then expand into other fintech products. The tech Miden is building is clearly in demand: The startup said it is already profitable and seeing strong traction so far.
Who picked: Becca
Oma Care
What it does: Helps pay family caregivers.
Why it’s a fav: The caregiving market is growing, and there is a massive opportunity — and demand — to make such a daunting experience flow a bit easier. I liked this app because there have been studies that show that caregiving duties most often fall on women, as they are more than twice as likely to be caregivers compared to men. Most often, they do not get paid for this, adding to the stat that women’s unpaid labor globally is worth more than $10 trillion. I welcome anything that tries to address this issue, and I’m excited to see more innovation in this space.
Who picked it: Dom
Garage
What it does: Marketplace for used fire-fighting equipment
Why it’s a fave: This is such a neat idea! Outfitting one firefighter is a couple thousand dollars, so creating a way for these departments to get gear without spending a lot of money seems smart. That’s especially true, considering you wouldn’t want budget concerns to prevent fire stations from getting their firefighters the safest gear. Sometimes good ideas for technology aren’t complicated.
Who picked: Becca
PointOne
What it does: Al-powered time tracking and billing for lawyers
Why it’s a fave: PointOne co-founder Adrian Parlow, who was previously an attorney at Fenwick & West, says that one of the worst parts of being a lawyer is having to track time in six-minute increments. I am not a lawyer or a paralegal, but I imagine figuring out how many fractions of an hour went to each client is tedious and time consuming. PointOne claims that advances in AI can automate timesheet generation by capturing work done on lawyers’ laptops and computers. I am a big fan of all applications that reduce professionals’ busy work. Now can somebody figure this out for filing expenses?
Who picked: Marina
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