Batch-level trend analysis
Breaks down 793 YC companies across five batches and summarizes the main shifts over time, including AI share, B2B share, team size, and hiring activity.
A data analysis product that examines 793 Y Combinator companies and 1,625 founder bios across five batches to surface patterns in AI depth, founder backgrounds, crowding, and batch composition. It is aimed at readers who want a structured view of YC funding trends rather than a company directory.
What YC Is Really Betting On is a data analysis product that examines 793 Y Combinator companies and 1,625 founder bios across five batches, covering Winter 2025 through Winter 2026. It organizes the cohort into views such as AI vs. non-AI, founder archetypes, competitive overlap, hiring signals, naming patterns, and partner preferences.
The homepage frames the product as a structured trend analysis rather than a directory or marketplace. Its purpose is to help readers understand what kinds of startups YC is funding, how those companies cluster, and which patterns stand out across the batches.
Breaks down 793 YC companies across five batches and summarizes the main shifts over time, including AI share, B2B share, team size, and hiring activity.
Classifies AI companies into wrappers, applied AI, AI infrastructure, and deep tech so readers can see how much of the batch is technical depth versus thin application layers.
Maps founder background signals such as ex-FAANG and PhD experience, plus team composition and location patterns like San Francisco concentration.
Identifies statistical relationships such as sector correlations, hiring patterns, and naming trends to highlight non-obvious patterns in the dataset.
Measures competitive crowding by vertical and flags especially crowded or unusually unique companies within the batches.
Groups companies into NLP clusters and pattern-based archetypes, including partner fingerprints and thematic segments like founder DNA and the archetype view.
Useful for people who want a compact read on what YC is funding across recent batches, especially when comparing AI, B2B, and deep-tech concentration over time.
Helpful for founders or operators who want to see how YC companies are grouped by archetype, naming patterns, and competitive crowding before positioning a startup.
Relevant for investors, analysts, or journalists looking for quantitative evidence about founder backgrounds, company mix, and cluster-level patterns in YC cohorts.
Useful when you want examples of companies in crowded or unusual categories, since the analysis includes representative companies for wrappers, applied AI, infrastructure, and deep tech.
The site presents an analysis of 793 Y Combinator companies across five batches, from Winter 2025 through Winter 2026. The homepage does not describe a separate setup flow or login-based workflow.
The published analysis focuses on company mix, AI depth, founder backgrounds, competitive overlap, naming patterns, hiring signals, and partner fingerprints. It is intended for readers who want a structured view of YC batch trends rather than a general company directory.
The homepage highlights analysis of 793 companies and 1,625 founder bios, along with NLP clustering, cross-correlations, and competitive overlap. It does not mention an export format or downloadable dataset on the page text provided.
The site text does not show pricing information, and the pricing page resolves to a 404. Based on the available evidence, pricing is not disclosed on the public pages provided.
Hype is a web tool for finding trending YouTube topics by category, time range, and scoring mode. Spot emerging ideas and review source videos.
Shengsuanyun offers cloud-based solutions for efficient data management and analytics.
Ranpo AI Visibility is a generative search analytics platform that checks how a brand appears in AI search systems such as ChatGPT and Gemini. It helps teams measure visibility, compare against competitors, and identify gaps that may affect inclusion in AI-generated answers.
PromptScout tracks how ChatGPT, Gemini, Google AI Overviews, and Perplexity mention your brand or competitors, then pairs those results with source analysis and website audits. It helps teams decide what to fix in content, positioning, or site readiness next.
SaveMRR is a Stripe retention tool for SaaS teams that scans billing data for churn and MRR leaks, then automates recovery through dunning, cancel-save offers, win-back emails, and onboarding nudges. It is built for founders and bootstrapped teams using Stripe.
Sleek Analytics is a privacy-friendly web analytics tool with real-time visitor tracking, Core Web Vitals, and revenue attribution. It helps site owners understand traffic and conversions without cookie banners or a heavy setup.