Analyzing Latest 400 Business Ideas funded by YCombinator

Trends, insights, and actionable takeaways on what to build with AI

8 min readJan 26, 2025

From https://highsignalai.substack.com/p/what-400-yc-backed-startups-reveal

82% of YC’s latest startups are AI-focused. Yet most founders are still building in overcrowded spaces, missing massive opportunities in untapped markets.

Six months ago, my analysis of YC’s previous cohorts helped many people spot emerging trends.

This time again, I’ve analyzed 400 companies from YC’s last three cohorts to decode what gets funded in 2025.

The patterns are striking: while 144 companies build AI agents, only one targets last-mile delivery — a $200B market.

Here’s what this analysis gives you:

Spot Emerging Trends: See which industries, technologies, and business models YC is betting on in 2025 and beyond.
Avoid Oversaturated Markets: Learn which AI verticals are crowded (like AI agents) and where the untapped opportunities lie (like last-mile delivery).
Validate Your Startup Idea: Find out what problems YC-backed startups are solving — and where you can carve out your niche.
Understand YC’s Priorities: Discover why 82% of funded startups are AI-focused and why B2B dominates the landscape.
Access Actionable Data: Get a clean, structured CSV file to run your own analysis and make smarter, data-driven decisions.

Whether you’re applying to YC or building the next big thing, this report will help you spot opportunities others miss. Let’s dive into what works.

Key findings upfront:

82% are AI companies, signaling YC’s clear priority
69% target B2B, showing enterprise is where the money flows
SF Bay Area houses 62%, but remote teams are rising

Let’s dive into the data and find your winning strategy.

Data

I collected the data from YC’s Startup directory for latest startups that got accepted in the Summer 23, Fall 24, Winter 25 cohorts.

The data required cleaning and some transformations to extract the tags they have and rechecked it from the description of the company to capture their main category.

I got 396 companies in the data with their description, urls, tags / categories, active founders, and founders’ bio.

If you need this data for your own analysis, you can get your copy from here.

While looking at a subset of these companies, I have found many exceptional use cases of AI.

Now, let’s unpack what’s working in YC.

⚠️ Disclaimer: Some parts of this report is generated with the help of LLMs and the numbers are approximate.

AI vs Non-AI

AI isn’t the future — it’s the present.

At this point, there are only 2 types of companies, ones that are building around AI and others that are not.

Original post: https://highsignalai.substack.com/p/what-400-yc-backed-startups-reveal

82% (325) of YC-accepted companies in the last 3 cohorts are AI-focused.
Non-AI startups are a declining minority with only 18% (71) companies getting accepted.

A strong data point for anyone planning to apply for YCombinator’s newly announced Spring cohort. This shows they are inclined to accept more applications from AI companies.

Having established AI’s dominance, we explore how business models (B2B vs B2C) shape startup strategies.

B2B vs B2C

69% (273) of startups target enterprises and developers, like Tabular (accounting automation) and Mem0 (LLM tools).
Just 17% (69) focus on consumers, with apps like pap! (personal finance) and BeeBettor (sports betting).

B2B (273 companies, 69% of total) Dominant Verticals:

Developer Infrastructure:

Tools for AI development (e.g., Mem0’s LLM memory layer)
Security solutions (e.g., ZeroPath’s vulnerability detection)
Data infrastructure platforms

Enterprise Software:

Workflow automation (e.g., Tabular’s accounting automation)
Business intelligence and analytics
Compliance and risk management

Industry-Specific Solutions:

Healthcare providers
Financial institutions
Manufacturing optimization

B2C (69 companies, 17% of total) Dominant Verticals:

Personal Finance:

Money-saving tools (e.g., pap!’s automated savings)
Investment platforms
Personal financial management

Consumer Apps:

Productivity tools
Entertainment (e.g., BeeBettor)
Personal wellness

Consumer Services:

Healthcare services
Educational tools
Lifestyle management

Hybrid (54 companies, 14% of total) Common Patterns:

Marketplace Models:

Connecting businesses with consumers
Two-sided platforms
Shared economy solutions

Multi-stakeholder Platforms:

Healthcare platforms (serving both providers and patients)
Educational platforms (serving institutions and students)
Real estate platforms (serving agents and buyers)

Key Trends and Insights:

1. AI Adoption Patterns:

B2B leads in overall adoption (83%)
Hybrid models show highest AI adoption (87%)
B2C shows lowest but still significant adoption (74%)

2. Investment Focus:

Heavy concentration in B2B (69% of companies)
Suggests stronger monetization potential in enterprise market
Higher barriers to entry in consumer market

3. Market Opportunity Signals: B2B Opportunities

Infrastructure for AI deployment
Vertical-specific AI solutions
Enterprise automation platforms

YC prioritizes B2B startups with clear enterprise monetization paths — critical for founders eyeing the Spring cohort.

Industry Breakdown: Sector-Specific AI Transformation

1. Developer Infrastructure (70 companies)

86% of the YC-accepted dev infra companies are building around AI.
Focus: Development tools, cloud infrastructure, DevOps.
Example:
Mem0 — Memory layer for LLM applications.
Pipeshift — Cloud platform for fine-tuning and inferencing open-source LLMs

2. Healthcare (47 companies)

83% of these 47 companies are solving problems with AI.
Focus: Clinical trials, drug discovery, medical billing.
Example:
Taxo — AI-powered medical billing automation.
Pharos — Automated hospital quality reporting systems.

3. Financial Services (46 companies)

70% these startups are automating processes for businesses with AI.
Focus: Accounting, payments, insurance
Example:
Tabular — AI Copilot for accounting firms
LedgerUp — AI RevOps platform that transforms contract-based billing

4. Education (41 companies)

95% of the education companies are AI companies.
Focus: Personalized learning, content generation
Example:
Capitol AI — Custom search and content platform
Edexia — AI teaching assistant that learns individual teacher grading styles

5. Retail (36 companies)

72% are AI companies.
Focus: E-commerce, consumer experience, product visualization
Example:
Presti AI — AI-powered furniture visualization,
AI Sell — AI Sales Associates for eCommerce with video interface

Key Patterns from Industry Distribution:

AI Adoption by Sector

Leaders: Legal (100%), Education (95%), and Media (91%) — loosely regulated sectors that are embracing AI for efficiency.
Laggards: Manufacturing (61%) and Agriculture (50%) — complex workflows and slower tech adoption.
Average Penetration: ~80%, signaling AI’s broad-based integration across industries.

2. Dominant Industry Focus

Infrastructure & Tooling: Largest sector, driven by demand for AI development frameworks.
Healthcare & Financial Services: Strong traction due to high-value use cases (e.g., clinical trials, fraud detection).
Climate Tech: Emerging hotspot, with AI optimizing energy and sustainability workflows.

3. Business Model Shifts

B2B Dominance: Enterprise solutions rule, targeting workflow automation (e.g., compliance, accounting).
Vertical Specialization: Surge in industry-specific AI tools (e.g., legal document automation, medical billing).

4. Innovation Frontiers

Traditional Industries Reborn: Legal and healthcare sectors reinvented via AI-driven efficiency (e.g., automated compliance, drug discovery).
Infrastructure Buildout: New tools for deploying AI at scale (e.g., LLM memory layers, cloud infrastructure).
Domain Expertise + AI: Convergence creating defensible moats (e.g., AI-powered mining optimization, agricultural yield analytics).

Technology Sector Distribution

AI Agents & Copilots (144 companies, 36.4%)

Focus Areas:
Business process automation (e.g., Tabular)
Consumer automation (e.g., pap!)
Industry-specific assistants (e.g., Plume)
→ Crowded Space: Highest competition but massive market opportunity. Strong potential for specialized solutions.

2 . Developer Tools & Infrastructure (76 companies, 19.2%)

Focus Areas:
LLM development tools (e.g., Mem0)
Code security (e.g., ZeroPath)
AI infrastructure (e.g., Lumen Orbit)
→ Highest Competition density: Strong focus on AI development tools and infrastructure.

3. Fintech Tools (66 companies, 16.7%)

Focus Areas:
Compliance automation (e.g., Focal)
Investment analytics (e.g., Bayesline)
Insurance tech (e.g., SureBright)
→ Mature: Well-funded competitors with established products.

4. Healthcare Tech (54 companies, 13.6%)

Focus Areas:
Clinical documentation (e.g., Baseline AI)
Medical billing (e.g., Taxo)
Health records analysis (e.g., RiskAngle)
→ Growing: Significant regulatory barriers but high potential.

5. Data & Analytics (27 companies, 6.8%)

Focus Areas:
Business intelligence
Process analytics
Performance monitoring
→ Competitive: Especially in enterprise data analysis.

Emerging Technology Sectors:

Real Estate/PropTech (13 companies, 3.3%)

Underserved market
Complex workflows
High value transactions

2. Biotech Research (10 companies, 2.5%)

High barriers to entry
Significant technical requirements
Large market potential

3. Design Tools (8 companies, 2.0%)

Creative AI applications
Visual content generation
Design automation

4. Legal Tech (7 companies, 1.8%)

Wide-open opportunity
High regulatory complexity
Large market potential

The number of startups building around AI Agents is living upto the hype. As many people are claiming that 2025 is the year of AI Agents, here’s a deep-dive on AI Agents companies.