Update: This project has since shutdown, but it was a lot of fun building it! We got accepted into Z Fellows, made it to YC interviews, and learned a tremendous amount about the data science ecosystem.
flockfysh was the ultimate solution to the dataset problems faced by data scientists, machine learning engineers, and researchers.
The Problem
The dataset problem is one of the biggest pain points in machine learning and data science. The process of collecting, cleaning, and preparing data for machine learning models is incredibly time-consuming and tedious.
Most data scientists spend 80% of their time on data preparation and only 20% on actual analysis and modeling. This is inefficient and prevents data scientists from focusing on what they do best - extracting insights from data.
The Solution
flockfysh provided an automated data collection platform that allowed data scientists to:
- Automatically collect relevant data from multiple sources
- Clean and preprocess data using AI-powered tools
- Version control datasets with Git-like functionality
- Collaborate with team members on data projects
- Deploy models directly from the platform
Key Features
Automated Data Collection
Our platform could automatically scrape and collect data from websites, APIs, databases, and other sources based on user specifications.
AI-Powered Data Cleaning
We used machine learning algorithms to automatically detect and fix common data quality issues like missing values, duplicates, and outliers.
Dataset Version Control
Like Git for code, we provided version control for datasets, allowing teams to track changes, branch, and merge datasets.
Collaborative Workspace
Teams could share datasets, annotations, and models in a collaborative environment designed for data science workflows.
The Journey
Building flockfysh was an incredible learning experience. We:
- Got accepted into Z Fellows - A highly selective fellowship program
- Made it to YC interviews - Reached the final interview stage at Y Combinator
- Built a working product - Created a full-featured platform with paying customers
- Learned about enterprise sales - Discovered the complexity of selling to large organizations
Lessons Learned
- Product-market fit is everything - We built a great product but struggled to find the right market fit
- Enterprise sales are slow - B2B sales cycles are much longer than we anticipated
- Technical execution isn't enough - Great engineering needs to be paired with strong go-to-market strategy
- Team dynamics matter - Building a startup is a marathon, not a sprint
What's Next
While flockfysh didn't achieve the scale we hoped for, the experience taught us invaluable lessons about building products, finding customers, and scaling teams. The data infrastructure space continues to evolve rapidly, and many of the problems we identified are still being solved by new companies.
The journey was worth it for the learning experience alone, and I'm grateful for the opportunity to have worked on such an ambitious project with an amazing team.