I’m Salah, founder of Repixa (AI demo reps for B2B SaaS).

I went through a large number of public startup failure cases and extracted the ones that showed clear operational and go-to-market breakdowns, not just vague “market timing” excuses.

Different industries.

Different regions.

Different funding levels.

Yet the same structural mistakes kept appearing.

So I organized 20 failed startups into this dataset to surface the patterns that quietly kill companies while everything still looks “fine” from the outside.

This is not theory.

This is what actually happens to real teams.

🧭 How to use this dataset

If you’re already running a startup, use this in two ways:

1. Pattern scanning

Look at Cause of Death and Lessons to see the failure modes that repeat across industries.

2. Model comparison

Find companies close to your own business model and study:

• What assumptions failed
• Where execution collapsed
• Which constraints killed their ability to adapt