knowledge graph engine for enterprise software Open source- 125k+ GitHub⭐️ backed by @ycombinator

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Joined June 2024
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Graphify Labs (YC S26) retweeted
love this. we’ve been doing formal verification at graphify too, just from the opposite direction. instead of modeling your system in tla+, we use the previous version of your code as the spec. on every pr, each changed function is checked against its old version: an smt solver either proves they’re equivalent or finds the exact input where behavior changed. for rust and c we use kani and cbmc, and when a proof can’t reach, we fall back to symbolic execution and real inputs from your own tests. if you’re new to this, think of it as differential verification. instead of writing a separate model and proving your code matches it, you treat the last version of the code as the relative specification. the question becomes “does this change preserve behavior, or did something shift?” an SMT solver either proves they’re the same or hands you the exact input, old value, and new value. historically formal verification never reached mainstream status because of the difficulty in modeling and writing proofs. it’s quite difficult to model your business requirements and keep them in sync! but using the previous version as the spec sidesteps that. there’s nothing extra to maintain. in the meantime we’ve been running this on real prs and it’s already catching behavior changes, with the input, old value, and new value right in the review.
pstack v0.15.27 ships with a new skill /create-formal-verification-skill! it's still in beta, and similar to /create-verification-skill, this is a meta-skill that creates a new skill and formal verification suite based on the characteristics you want to verify. for example, you may want to model state machines and systems with concurrency using TLA+, or use kani in rust to check for undefined behavior. if you're new to formal verification, think of it as mathematically proving properties and invariants (something that must always be true) or "laws" of your system. usually, this means modeling your programs in a separate language like with TLA+ and then running the solver on that spec. newer approaches like with kani and @bendlang take a different approach where there is no separate language: you write kani in rust, and bend in bend (it's also a programming language, and the proofs are written as laws and expressed in its type system). historically formal verification never reached mainstream status because of the difficulty in modeling and writing proofs. it's quite difficult to model your business requirements and keep them in sync! but i expect that we will see more innovation in formal verification in the future as being able to formally verifiy that the code does what you intended gives your agents superpowers in writing correct software. in the meantime though, i've been experimenting with modeling our code with TLA+ and have already found several bugs with the skill created by /create-formal-verification-skill. try it out and let me know how it goes!
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We love talking with agents
MCP is the heart of Graphify’s self-hosted product. Growing 30%+ week over week and nearing 4M calls a month.
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Graphify Labs (YC S26) retweeted
been thinking about this a lot. a year ago id open a PR and force myself to read every line even when i was tired. now the agent writes the change, runs the proofs and can push to main before ive even finished the thread. easy path is cognitive surrender. you stop tracking what the systems actually doing and just approve whatever comes back coz the tests passed. harder path is staying in cognitive engagement. not scanning diffs. holding the longer picture in your head and deciding which direction was actually worth taking before the agent even starts. thats the real shift. not whether code review disappears. whether we stay engaged or slowly check out.
No pull requests, no code review. We push to main. Our agents read production logs, watch deploys, grant feature flags, and check their own work end to end. Here's how we do that:
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Graphify Labs (YC S26) retweeted
I was just watching this kaparthy video about how LLMs is bad at counting and math cuz it has to compute everything in a token. I think about graphify and what makes it work is you are looking at code. Code is truth and you are turning it each a semantic roadmap for the LLMs. This is what makes it work. You’re taking the part LLMs are bad at and making it magical. Same logic why Jev is taking off and why people mix markdown with scripts. Graphify is that trust layer for agents. But people have to trust it before they can give into it. Actionable insights, finding bugs, making migrations faster, reducing tokens. Each delivery is one more trust item
I truly don't understand why nobody is using this setup graphify, a tool that turns any folder into a knowledge graph your agent can query, just passed 126k stars on github and got into Y Combinator. people stopped asking ai questions. they're giving it a desk, a memory and a job. you give Claude Code one folder, plug in your email, calendar and a browser, and it turns into an agent. it reads, remembers, acts, and checks itself before it does anything stupid. doesn't matter if you're a founder, a marketer or a student, you need this the full setup: > create a folder called AGENT, open Claude Code inside it and add a CLAUDE.md with one rule: "save every decision, person and project to memory/" > run npm install -g @googleworkspace/cli, then gws auth setup. now it reads your Gmail, Calendar and Drive > run claude mcp add playwright npx @playwright/mcp@latest. it gets its own browser to open sites, fill forms and pull data for you > run uv tool install graphifyy, then graphify install, then type /graphify .. everything in the folder becomes a knowledge graph it queries in seconds instead of digging file by file > run npm i -g jev-guard, jev-guard key "...", jev-guard install claude. a tiny model called Jev scores every action before it runs. rm -rf gets blocked, a poisoned email gets flagged, for about 4 cents per 1,000 checks > type /schedule and tell it "every morning at 7:30, send me what came in, what you drafted and what waits for my yes". from now on it works on a routine 15 minutes to set up, and you never start from a blank chat again. every repo is below: -> github.com/googleworkspace/c… -> github.com/microsoft/playwri… -> github.com/Graphify-Labs/gra… -> github.com/leepokai/jev-guar… bookmark this
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As they say, own the distribution
Sometimes I wonder how this happens. You ship a tool that actually solves a real problem and your users just start becoming the marketing. One post using Graphify just cleared 300k views. There are 1000+ videos about it across social media. I’ve spent $0 on ads. Open source got us the initial distribution. Users are now doing the rest.
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Build Talk to customers Iterate Repeat
We implemented a direct flywheel enhancement. Learn A -> Fix A -> Metrics movement B, keep repeating and it compounds Recorded our maximum DAU yesterday - > 1,771 and max retention of 7.27% with 600 signups in single day
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Connect your repos and see which ones actually move together. Then give that context to every agent you run. Try the feature: app.graphify.com
An agent's real bottleneck is cross-repo context, not how your code is organised. Graphify surfaces that context with a code graph showing which repos change together. Add incident memory on top and you can govern the agentic SDLC
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Graphify is now available on the @Vercel Marketplace! With this integration, your coding agents get a live knowledge graph of your Vercel app’s codebase, so they understand your code before they change it, at a fraction of the token cost.
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He thinks he’s Flash
Graphify is growing fast, we had our maximum all time DAU yesterday (1500+) and maximum signups in a single day (500+) 94k+ code reviews in last 30 days and 67k+ Formal proofs runs on PRs 6 enterprise deals in motion 23.5k+ users signed up on app.graphify.com All with a lean team, a solo founder and 7 weeks since launch with a free GTM ( our Open Source)
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A huge thanks to the 300+ contributors of Graphify
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Graphify Labs (YC S26) retweeted
They say if you can sell your product to the agents, you’re winning. 2.2M MCP calls in the last 30 days at @graphify
Remember when people said MCP was dead? We launched 6 weeks ago. Nearly 2M calls in September.
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Graphify is celebrating the milestone of reaching 125,000 GitHub stars!! This is an achievement of our whole community! Thank you for every star, every pull request, and all the time you put into making Graphify better. We are lucky to build this open source project with you all ♥️
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Graphify Labs (YC S26) retweeted
The reason we hit 22,000+ users in 7 weeks is open source traction turning into real product users. All bottoms up PLG. Biggest advice to founders: build in public and get the distribution. It compounds. Oh btw we’ve hit another milestone on open source of @graphify with 125k GH stars
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7 weeks in and this is our highest daily active users so far. 1,223 yesterday. To mark the milestone, annual plans are 30% off. Onboard: app.graphify.com
Highest DAU we’ve hit in 7 weeks of launch. 1,223 users yesterday To mark the milestone, we have got something in the comments.
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Graphify Labs (YC S26) retweeted
Cleanest free @graphify setup I’ve seen so far Ollama + Claude Code, fully local
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Replying to @sumitp01
This is awesome!
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