Pear VC is a prominent pre-seed and seed-focused venture firm that has been running accelerators with about 10 startups in each batch for about 10 years.
Over the years, this small but mighty program has led to companies like Viz.ai (valued at $1.2 billion in 2022), which allows FDA-approved AI to diagnose stroke, and Relationships, which raised $80 million in Series C. He has helped launch numerous companies, including management company Affinity. Valar Labs, valued at $620 million, according to PitchBook data, uses AI to help doctors make cancer treatment decisions. (We closed a $22 million Series A in May.)
This year, Pear decided it was time to expand the accelerator and offer more services by offering companies recruitment assistance and space in its new 30,000 square foot San Francisco office. Going forward, the 14-week program, currently called PearX, will be run twice a year. Each batch consists of approximately 20 companies. This massive program is still a far cry from Y Combinator's program, which admits hundreds of startups a year.
The difference between PearX and YC is not just in smaller size. Start-up for each batch is typically not revealed until Demo Day. Demo Day is an in-person event with more than 100 VC general partners, including top firms such as Sequoia, Benchmark, and Index Ventures. While YC says it offers the same standard terms to each company, the funding PearX startups receive from the company could range from $250,000 to $2 million, depending on their needs and stage of development. That's what it means.
This year's Demo Day, held earlier this month, attracted 20 companies, most of which focused on AI. Here are five that caught our attention and those in attendance for their innovative approaches to complex business problems.
Neutrino AI
Capability: Identify the best infrastructure for multi-model AI applications.
Why it stands out: AI companies want to make sure they have the best tools for the job. Determining which LLM or small language model is best for each application can be time-consuming, especially since these models are constantly changing and improving.
Nuetrino wants to make it easy for AI companies to find the right combination of models and other systems to use in their applications. This allows developers to work faster and save money on running their products.
Kuno AI
Features: Automate market research.
Why it stands out: Brands spend millions of dollars each year on market research. The process of researching potential customers takes time. Quno AI agents can call customers and collect qualitative and quantitative data. Results can be analyzed in real time. The bonus is that AI can quickly analyze the results of these conversations.
Resiquant
Description: Develop a catastrophe model for home insurance companies.
Why it stands out: With natural disasters on the rise, property and casualty insurance companies are struggling to identify which homes are most at risk of significant damage in the event of a major disaster. This is because information about home construction is difficult to access and expensive to obtain.
Founded by two structural engineering PhDs, ResiQuant creates models to estimate the characteristics of buildings and how they will withstand earthquakes, hurricanes, and fires. The company claims it will allow insurance companies to more accurately assess risk, potentially lowering premiums for homeowners deemed to be at lower risk.
self-evaluation
Function: Monitors actual production and alerts operators to mistakes.
Why it stands out: Investigators say a Boeing 737 Max door exploded mid-flight in January because four critical bolts were missing. This situation is just one high-profile example of what can go wrong within a quality assurance system. However, manufacturers of all types of products have similar needs to detect defective products before they leave the factory.
Self Eval hopes to address these concerns by using cameras and AI to ensure tasks are completed correctly and flag manufacturing errors in real-time.
teach share
Content: Create lesson plans tailored to each teacher's needs.
Why it stands out: Software that adjusts difficulty based on individual student knowledge has been available for some time. However, TeachShare's founders argue that many education companies still offer a one-size-fits-all approach to curriculum development. As a result, teachers must spend a significant amount of time modifying lesson plans to suit their specific classrooms. TeachShare aims to help teachers adjust their daily content and ensure alignment with educational standards.