Git Deal Flow
Harmonic.ai
DealRoom
Forager
Crunchbase
Bolt to GitHub (Pro)
Equity Flow
Flowbo
Algorithmia
MCenter
5Analytics
Spell
neptune.ai
MuleSoft Anypoint Platform
Zapier
Datadog
VC Deal Flow Signal monitors GitHub engineering activity across thousands of startups and surfaces the ones showing unusual acceleration — 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.
Git Deal Flow AlgorithmiaAlgorithmia is recommended for data scientists, machine learning engineers, and developers who need a flexible and scalable environment to deploy, manage, and share AI and machine learning models. It is particularly suitable for teams seeking to collaborate and leverage pre-built algorithms from a community-driven marketplace. Businesses looking to integrate machine learning capabilities into their operations without extensive infrastructure management will also benefit from Algorithmia's offerings.
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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, Algorithmia should be more popular than Git Deal Flow. It has been mentiond 5 times since March 2021. 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.
I publish the weekly top movers in a free Sunday email at gitdealflow.com. The heavier stuff (full rankings, sector sweeps, dashboards) is paid, which is what funds the compute. - Source: dev.to / 25 days 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 / 4 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 / 5 months ago
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 4 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 4 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: almost 5 years ago
Seems similar to https://algorithmia.com. Source: almost 5 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / about 5 years ago
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.
MCenter - Machine Learning Operationalization
DealRoom - M&A Lifecycle Management Software
5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.
Forager - Fashion discounts gathered in your size
Spell - Deep Learning and AI accessible to everyone