LangevinAI – Automated FP&A for Everyone

Hacker News

Hi everyone, I built this tool based on my experience as a financial controller at a Fortune 500 company. The idea is to automate most of the analysis work. All it needs is a general ledger, and you can add other relevant documents if needed(emails, contracts, loan sheets, etc) I'm trying to make it work with most GL formatting, even the messy ones you can't even filter on Excel(like with Yardi, the ERP I used at my last job). Then you get a dashboard, KPIs and most importantly variance commentary that's also going to tell you if something is potentially incorrect and why. I also wanted to make sure no onboarding, connection or setup was required, it only works with stuff you already have. I'm intrigued to see if this could be useful beyond the very niche context I built this around(3/4 teams working together, different tools, a lot of info circulating through emails & meetings, stiff organization & Chinese walls). Maybe for SMBs, founders, fractional CFO, etc. It was a first for me to build something so "complete"(if you haven't guessed yet, I'm not exactly technical), having to setup a database, deployment, authentification, payments and of course API calls for the AI features. The platform itself is just a webapp with no persistence. There's a free tier with 3 analyses for you guys to try.

Visit product View on Hacker NewsJun 30, 2026

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: email, context · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

22%22% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

18%18% 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.

Correct prediction on native model

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