NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
Figure Eight
Git Deal Flow
Harmonic.ai
DealRoom
Forager
Crunchbase
Bolt to GitHub (Pro)
Equity Flow
Flowbo
VC Deal Flow Signal monitors GitHub engineering activity across thousands of startups and surfaces the ones showing unusual acceleration โ weeks before they hit your inbox.
We track commit velocity, contributor growth, and repository expansion to rank startups by engineering momentum. This is a leading indicator for seed and Series A investors.
What you get: - Weekly ranked reports of breakout startups across 20 sectors - Real GitHub acceleration data (not vanity metrics) - Filter by sector, stage, and geography - Live dashboard with 100+ startups tracked
Who it's for: Angel investors, VCs, and fund analysts looking for deal flow signals that aren't in everyone else's pipeline.
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Git Deal Flow's answer:
We use GitHub engineering activity as a leading indicator for investors. While competitors like Harmonic, Dealroom, and Crunchbase rely on funding announcements, job postings, and web traffic, we track commit velocity, contributor growth, and repository expansion - signals that appear weeks before a startup shows up on anyone's radar. The data is public but nobody else packages it for investors.
Git Deal Flow's answer:
Most deal flow tools show you what already happened - a round closed, a hire was made. We show you what's happening right now in the codebase. Engineering acceleration has historically preceded fundraise announcements by 3-6 weeks. That's the difference between setting terms and chasing a deal everyone already knows about.
Git Deal Flow's answer:
Angel investors, seed and Series A VCs, fund analysts, and scout networks looking for data-driven deal sourcing. Anyone who wants to find breakout startups before consensus forms around them.
Git Deal Flow's answer:
I watched a company's commit graph spike and three weeks later they announced a Series A. The signal was right there - public, free, updating in real time. Nobody was reading it. Quant funds have known for years that public data read correctly is the best leading indicator. The problem was that nobody built the lens for investors. So I did.
Git Deal Flow's answer:
GitHub API for data collection, Next.js for the dashboard, Vercel for hosting, and custom algorithms for detecting acceleration patterns across thousands of startup GitHub organizations.
Git Deal Flow's answer:
Based on our record, NumPy seems to be a lot more popular than Git Deal Flow. While we know about 122 links to NumPy, we've tracked only 2 mentions of Git Deal Flow. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Unmatched integration with ML/AI ecosystems through NumPy, TensorFlow, and PyTorch. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
AI starts with math and coding. You donโt need a PhDโjust high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI, thanks to tools like TensorFlow and NumPy. If you know JavaScript from Vue.js, Pythonโs syntax is straightforward. - Source: dev.to / 12 months ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / over 1 year ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / almost 2 years ago
Quick context: I run GitDealFlow, an MCP server + dataset that tracks GitHub commit-velocity signals across ~100 venture-backed startups. Six free read-only tools, ~700 npm downloads in the first three weeks, listed on Glama and the official MCP registry. - Source: dev.to / 3 months ago
VC Deal Flow Signal monitors GitHub engineering activity across startup organizations and surfaces the ones showing unusual acceleration. The hypothesis: engineering acceleration (measured as the rate of change in commit velocity) is a leading indicator for fundraise announcements, usually by 6 to 12 weeks. - Source: dev.to / 3 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Harmonic.ai - Harmonic's data engine keeps 20M+ companies & 150M+ professional profiles fresh, so you can always be in the loop when a company just raised a round, just hired a CTO, or just crossed the 1M follower mark on Twitter.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
DealRoom - M&A Lifecycle Management Software
OpenCV - OpenCV is the world's biggest computer vision library
Forager - Fashion discounts gathered in your size
