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Venice – open-source Plaid to Postgres in minutes without code

Hacker News

Venice – open-source Plaid to Postgres in minutes without code

Hi HN! Tony & Ali here, we are super excited to introduce Venice - an open source financial data integrations platform. Our MVP is getting financial data from Plaid into your postgres database in under 5 mins. We met while building our own respective fintechs. We noticed how much developer time went into setting up and maintaining the infrastructure rather than actually building the fintech itself. In Tony’s last project Alka for instance, the engineering team spent 30%+ of time building and maintaining the data connectivity and pipeline rather than the core work of accounting. What we wish existed is a Segment / Airtable for fintech, letting you get financial data from wherever they are produced to anywhere they are useful. We think the most basic version is a Plaid to Postgres database connector with a self-service portal where your customers can add / remove / repair and manage their financial connections. This takes less than 5 mins to set up without writing a single line of code. In fact, we went so far as asking non technical people to get set up and they were able to do it just as fast using Vercel, Supabase and Plaid. Today, our product is perfect if you’re just starting out or using it as a hobby, but eventually we hope any sized fintech could use what we’ve built as the project matures and community grows. We wrote it using full stack TypeScript, and paid special attention to composability and extensibility. There is a core connect & sync library with its own cli, a HTTP API (thank you to the amazing folks at trpc + zod), a set of headless React components, theme-able data-connected UI library leveraging tailwindcss, and finally a next.js application that puts it all together. Each layer is built on the one before, so you can start with no code at all while drop down to any layer of abstraction as your need grow. What we are shipping today is a complete, instantly deployable next.js application which you can use either as a standalone portal via redirect, or embed into your application via iframe. The default setup uses Vercel as we expect you to bring your own database and authentication that powers the rest of your application. The repo is licensed under MIT & ELv2, so you are completely free to use it for your own projects and companies while we retain the right to being the only one to release a cloud hosted version in the future. Check us out at https://github.com/useVenice/venice . We have a ton of ideas in mind and would love your feedback. Hit us up at hello@useVenice.com or on slack at http://link.usevenice.com/slack

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, single, using · Missing: mac, agents, macos
94%94% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, open source · Missing: https docs, just released, lua
80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews
35%35% 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
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid, introduce · 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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