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The 18 most interesting startups from YC’s Demo Day show we’re in an AI bubble

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distorted Y Combinator logo on a background of jagged thick lines
Image Credits: Bryce Durbin/TechCrunch

Springtime means rain, the return of flowers and, of course, Y Combinator’s first demo day of the year. During the well-known accelerator’s first of two pitch days from the Winter 2024 cohort, a covey of TechCrunch staff tuned in, took notes, traded jokes and slowly whittled away at the dozens of presenting companies to come up with a list of early favorites.

AI was, not shockingly, the biggest theme, with 86 out of 247 companies calling themselves an AI startup, but we’re reaching bubble territory given that 187 mention AI in their pitches.

From AI-generated music and grant applications to neat new fintech applications and even some health tech work, there was something for everyone. We’re back at it Thursday for the second day of pitches. Until then, if you didn’t get to watch live, here’s a rundown of some of the best from day one.

TechCrunch’s staff favorites

Aidy

  • What it does: Uses AI to help companies find and apply for grants
  • Why it’s a fave: Landing grants isn’t easy. Max Williamson, Peter Crocker and Greg Miller know this well: They’ve worked between them at The Rockefeller Foundation and the U.S. Department of Housing and Urban Development, where grants are common currency. Finding and applying for grants involves sifting through mounds of paperwork and submitting countless forms — an expensive and time-consuming process. So why not have AI help with it? That’s the idea behind their startup Aidy, which is focused exclusively on Rural Energy for America Program grants for now. After asking a few questions, Aidy evaluates an organization’s competitiveness for grants by navigating eligibility requirements and scoring criteria, then takes a first pass at filling out any relevant forms. Aidy is clearly in the proof-of-concept stage, judging by the state of its tooling. But the concept’s an interesting one — assuming the platform’s AI doesn’t make too many mistakes.
  • Who picked it: Kyle

Givefront

  • What it does: Serves as a banking platform for nonprofits
  • Why it’s a fave: If you’re in the nonprofit space, compliance and regulatory requirements force you to do finances a little differently. That’s where Givefront comes in. Co-founded by Ethan Sayre and Matt Tengtrakool, who previously launched a startup to help loan-takers based in Nigeria, Givefront offers banking, spend management and financial governance services for nonprofits. Specifically, Givefront provides accounts to nonprofits to store money and integrate donations, payments and reimbursements, as well as features for automatic reporting and annual regulatory filings. Givefront certainly isn’t the only nonprofit banking option out there. But it appears to be one of the first built from the ground up for this purpose — which certainly has its own appeal.
  • Who picked it: Kyle

Buster

  • What it does: Software that links databases and large language models
  • Why it’s a fave: There’s a lot of attention in the market on companies that make large language models — the bigger, the faster, the smarter; you get the idea. But when it comes to actually deploying modern AL models inside of a company, you run into data issues. For example, Skyflow, one startup I covered recently, is working to keep sensitive information out of the wrong users of LLMs. Buster was eye-catching because it appears to be working on a problem that a whole mess of companies are going to run into. Sure, new models are cool, but selling software picks and shovels during the AI gold rush is probably a darn good business model. I dig it!
  • Who picked it: Alex

Numo

  • What it does: Banking services for contractors in emerging markets
  • Why it’s a fave: Creating better payroll solutions for remote and international workers isn’t new, but Numo’s approach of focusing on contractors in emerging markets specifically stands out. It’s also smart that Numo is building a banking product on top of its payroll system so that these contractors, many of whom would be based in countries with currencies that fluctuate frequently, have a more secure place to store their earned funds.
  • Who picked it: Becca

Intercept 

  • What it does: Uses AI to help consumer packaged goods brands aggregate retail fees and dispute invalid ones
  • Why it’s a fave: Many CPG brands, especially emerging ones, have very small margins that are squeezed by numerous fees that cover shelving, packing incorrect quantities and shipping damaged products. Intercept says that spotting and flagging invalid fees could give CPG brands back an average of 15% of their revenue that would have otherwise been spent on inaccurate fees. This seems like a problem worth solving.
  • Who picked it: Becca

Nuanced Inc.

  • What it does: Helps detect deep fakes and misinformation
  • Why it’s a fave: I’m curious about any technology that seeks to find ways to parse through the inevitable rise of deep fakes and misinformation we are already encountering. Artificial intelligence is becoming more sophisticated by the hour, and we are about to enter a world where right, wrong, fact and fiction have already started to get blurry. Deep fakes are of particular concern for women, as seen by what happened to Taylor Swift — and with slow government regulation in this space, I welcome any research and technology focused on trying to address our ever-increasing cybersecurity needs.
  • Who picked it: Dom

Vectorview

  • What it does: Custom LLM evaluation
  • Why it’s a fave: One of my favorite things to read through when a new, major LLM comes to market is its benchmark stats. For example, Anthropic’s Claude 3 Opus model has a 50.4% 0-shot CoT in “Graduate level reasoning, GPQA, Diamond.” It’s super clarifying stuff. Kidding aside, it’s not. That’s why I like the idea that Vectorview is working on, namely the ability to test LLMs and AI agents for a company’s particular use case. I suspect that by having its testing tools closer to the end user than the academic side of things, Vectorview could be onto something big.
  • Who picked it: Alex

Abel

  • What it does: Uses AI to help lawyers go through legal documents quicker
  • Why it’s a fave: Abel co-founder Sean Safahi said that this eliminates the need for lawyers to choose “depth over breadth.” I think any tech that helps lawyers make more informed arguments and decisions is a good thing. Speeding up the legal process and making it more accurate seems like a solid strategy. It’s worth noting that bringing AI and automation into the legal process does add a layer of privacy risk and users of Abel will have tread carefully.
  • Who picked it: Becca

Soundry AI, Sonauto

  • What they do: AI-powered music generation
  • Why they’re faves: Soundry AI’s technology could be incredibly useful to create music that sits neatly in the background. Muzak, elevator tunes, corporate learning soundtracks, whatever they play in loud restaurants that you can never quite make out, but might be a song that you know. It’s a big market, and I can see companies tuning their own mixes to get the right vibe. Then there’s Sonauto, a startup that wants to help you make hits. I am more skeptical here, mostly because the music I love the most takes a lot of humans working super hard to push the boundaries of what music can be. The latest Tesseract record is a good example. Goddamn, what an incredible piece of art. That said, I am open to being wrong here, and that the robots will eventually write better progressive metal and pop and experimental jazz than we humble meatsacks can. I love music, I love tech, so I presume that I am going to eventually love their union. (Though I also have copyright worries here regarding source material, I must add as I am no fun.)
  • Who picked it: Alex

Starlight Charging

  • What it does: EV chargers and management software for apartments, condos and commercial buildings
  • Why it’s a fave: Most EV charging happens at home, unless you live in a multifamily building, where infrastructure can be scant and forcing drivers to find power elsewhere. That’s not only a headache for drivers, it’s unrealized revenue for building owners. Starlight Charging centralizes key parts of the infrastructure to keep costs down. “Since our installation costs are so low, we can actually offer our solution for no upfront cost and still make money,” founder Andrew Kouri said. “Our payback period is less than one year. The company seems to be sweating the small stuff, too, offering its own charging equipment that adheres to the Plug & Charge standard for payments and comes with a removable cable that’s easy to swap in case of damage or vandalism. That should help with maintenance, something that’s tripped up many other EV charging networks.
  • Who picked it: Tim

Eggnog.ai

  • What it does: Online video creation and hosting for AI-generated clips
  • Why it’s a fave: I muted the Demo Day stream to give this a try — you can check out my creation here — because one thing I am constantly bummed out by is the dearth of new sci-fi films for me to watch late at night. We need more! So, video creation tools that lean on user prompts are super interesting to me. Mix in the fact that AI-generated stuff might not find a permanent home on mainstream video platforms (brand safety, copyright concerns, the list goes on), Eggnog could be onto something. Still, while my little video clip was neat, it is about as close to a feature film as my doodles are to the best animated series out there.
  • Who picked it: Alex

Pump

  • What it does: Bundles small businesses so they can save on AWS
  • Why it’s a fave: This is a great approach to help small and emerging companies get the cloud services they need without having to spend a significant portion of their capital on software. Pump’s decision to monetize through AWS, not the small companies themselves, is smart and makes it much more likely it could generate strong traction. It’s easy to get excited about a company called the “Costco of cloud compute.”
  • Who picked it: Becca

Pico

  • What it does: Seeks to organize screenshots
  • Why it’s a fave: It’s a favorite because I have, like, 13,000 photos on my phone, most of which are screenshots. And when I need to find a screenshot, I’m stuck searching through the abyss of my phone’s library. Having something that helps group these photos could be a lifesaver that allows me to attend to the important tasks, like sending out timely memes to the group chat. The founder billed this as Pinterest for screenshots, which also grabbed me as I am an avid Pinterest user. Anything that makes photo grouping and sharing easier and fun is a product I’m bound to use.
  • Who picked it: Dom

TrueClaim

  • What it does: Uses AI to help self-funded companies save 7% on health insurance
  • Why it’s a fave: Health insurance costs are skyrocketing. Large corporations can “eat” the fees, but absorbing the high cost is much harder for small and medium-sized businesses. SMBs are often forced to pass a large part of what they pay to their employees. Seven percent may not feel like a lot, but since health insurance can cost thousands of dollars a year, the savings could be meaningful for a small business or startup.
  • Who picked it: Marina

Manifold Freight

  • What it does: Aggregates spot freight
  • Why it’s a fave: The founders’ discovered demand for spot freight technology building a similar solution at Convoy and noted it was the only profitable part of the shuttered company that was snapped up by Flexport. Manifold Freight is focusing on companies that have 50 or more trucks, which means they are targeting a customer base that other freight software is overlooking. Plus, targeting larger carriers means their customers likely have more funds to spend on new technology.
  • Who picked it: Becca

Shepherd

  • What it does: Personalized teaching assistant that combines human tutors with AI
  • Why it’s a fave: I liked this because unlike other learning assistants, Shepherd works with academic institutions. This means the startup is not only authorized to tutor students, it also knows exactly what material needs to be learned. Shepherd also claims that it can help plan and manage students’ time. I would have liked to have had this when I was in college. It wasn’t always clear which learning task would be most challenging, and that ate up a lot of valuable time. Some of the countless hours I wasted learning to write code and get the program to work could have been better allocated to calculus, which wasn’t easy either.
  • Who picked it: Marina

Senso

  • What it does: AI-powered knowledge base for customer support in regulated industries, starting with credit units
  • Why it’s a fave: I hate being stuck on customer support calls. A conversation can seem to last forever as an agent puts you on repeated multi-minute holds to help figure out regulations or whatever other problems I’m trying to solve. If customer support specialists can quickly find an answer to an arcane regulation issue, it could save customers and banks (or insurance agencies) time and money.
  • Who picked it: Marina

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