We are building a production agent to turn your code into cloud infra

Hacker News

Hey HN, We've noticed a gap for small teams: getting a prototype working locally or on Vercel and Supabase is easy, but graduating to a full fledged deployment on a cloud provider is a nightmare. If you don't have a dedicated DevOps engineer, you're usually stuck clicking around hoping that some combination of checkboxes will do the trick . We're building Grafos V2 to act as your application's production agent. • You provide your application, optionally tell it what you need if its not obvious (e.g. I need a special type of MLOps or custom model garden models) and choose your cloud provider. • The agent understands the nitty-gritty details so you don't have to. • It outputs verifiable infrastructure code, using your repository to store the source of truth. We are opening a Closed Alpha to 100 users to test this out. If you're building anything and want your app productionized without the infrastructure headache, let us know in the comments or sign up in the link of the post

Visit product View on Hacker NewsMar 24, 2026

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, user · Missing: mac, agents, macos

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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