Unlock fast database management and resource optimization with our Git-inspired branching and versioning, making development cycles a breeze.
Joined August 2025
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40 Photos and videos
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22 Sep 2025
Today marks a special day for us!
We’re thrilled to announce our $2.1M pre-seed round to build the next layer of data collaboration between humans and AI agents
Huge thanks to our backers @SchematicVC, @skydeck_berkeley, and angels from @datadoghq , @OpenAI , @MistralAI & more
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Apr 21
We might have accidentally made the first digital hair loss prevention product for developers. And it's open-source.
The classic 3-in-1 is slammed on it: Instant DB branching, Instant rollback & versioning.
Working with AI agents is unavoidable, so at least do it stress-free.
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Apr 15
For all the release managers out there, listen:
Fresh DB clone for every PR, auto-provisioned.
Validate migrations against production-identical data.
PII masked at clone time with compliance by default.
Music for your ears? Then check gfs.guepard.run 👈
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Mar 19
Alexey Grigorev (DataTalks.club) gave Claude Code access to Terraform. The agent thought the infra looked wrong… and wiped everything .
In this demo, Yassine Ghorbel shows how GFS prevents that agents run on isolated database branches, not production.
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Mar 18
AI agents are smart, yet most teams still keep them away from their database.
That's where GFS comes in.
Every agent gets its own branch, its own sandbox to experiment in.
It can safely try, break, and fix things without any risk of data loss.
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Mar 17
This thumbnail is from a parallel universe where MrBeast is a tech bro.
What’s not from a parallel universe is Claude Code deleting a 2 and a half years database.
Ask Alexey, the founder of Datatalks,he felt that. Avoid this bad spot, work smart, use GFS github.com/Guepard-Corp/gfs
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Mar 11
3 reasons write agents scare prod 🧵
1/ Silent corruption > loud failure
Bad writes sit quietly wrong for days.
2/ Agents know schema, not invariants.
One delete lead to chaos later.
3/ Rollback is an illusion.
Other systems already read the data
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Mar 11
Agent's need git capabilities to work on data, fortunately you can grab them right here.
👉 guepard.run
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Mar 9
Nah.
AI agents can't be trusted with a shared staging DB that 3 other teams already used this Morning 🙂
Fix the environment before you blame the agent.
Isolated Realistic. Safe. guepard.run 😏
#AI #DataEngineering
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Mar 5
production is never even in the conversation 😌
Write whatever, break whatever. No risks no consequences.
Your Agent is done? The branch disappears, Like it was never there.
This is the Guepard experience
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Mar 3
You didn't ship a limited agent because of the model.
You shipped a limited agent because you were too afraid to test on real db The database was always the ceiling. 😏
We're building the fix at guepard.run curious what your current work around looks like ?
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Feb 27
real talk tonight 😏
What's the one thing that's been humbling you lately?
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Feb 19
3 secrets your database will never tell you: 🤫
It doesn’t like being cloned manually.
It loves to hide errors in prod.
It hates slow rollbacks.
Which one has caused your team the most headaches?
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Feb 16
What no one is saying out loud: The bottleneck isn't AI capability, it's that our databases were designed in 1960.
They assume humans make careful, considered changes. AI agents need to experiment at machine speed, hundreds of iterations, parallel scenarios, instant rollbacks.
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Feb 16
The companies winning the agentic era aren't the ones with better models. They're the ones who stopped treating data infrastructure like something fragile you protect, and started treating it like something you can fearlessly experiment with.
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Feb 3
Production isn’t fragile, it’s unforgiving.
Not because of skill, not because of bugs, because touching it feels like defusing a bomb.
This makes the best teams the ones that don’t avoid risk, but make the risk LOW-IMPACT.
What’s the riskiest change your team survived? 💣
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