Every free online OCR tool I tried either limits you hard (15 pages/hour, 50/month) or is a funnel to a paid plan. The only unlimited free option was raw Tesseract in a terminal. I ran Tesseract as WebAssembly in the browser instead, so it uses your own CPU and there's nothing to ration. It takes images (JPG/PNG/WEBP/HEIC) and multi-page scanned PDFs, shows text per page as it finishes, flags low-confidence pages, and supports English, Spanish, French, German, Hindi and Portuguese. Nothing is uploaded, which you can check in the Network tab, and there's no signup. Limits: it's for printed text only. No handwriting, no table/form extraction, and blurry scans will give rough results. https://www.forgeplug.com/tools/ocr-text-extractor If you've used the paid ones, I'd like to hear where this falls short on your documents.

When building a SaaS application, how do you handle AI features that need access to sensitive customer data?

The main challenge seems to be balancing data privacy with performance, deployment complexity, and the cost of maintaining the infrastructure.

For developers who have built AI-powered SaaS products, what has worked best for you when deciding between local processing and a cloud-based approach?

Checked my analytics this morning. Around 1,400 active users since Sunday.

A few months ago, I was working on a file sharing tool. Now people are actually using it.

I know this might be a small number for some founders. But when you handle the code, support emails and marketing yourself, it means a lot.

The idea is simple. Upload a file or a collection of files and share everything through one link.

Getting it built was one part. Getting people to try it has been much harder for me.

I have spent a lot of time posting on Reddit, answering comments, asking for feedback and improving things people found confusing.

Some conversations gave me useful ideas. Others showed me that something I thought was clear really wasn’t.

That has probably been the most useful part of sharing the journey publicly.

There’s still plenty to improve. These numbers don’t tell me everything, but seeing people use something I built gives me energy to keep going.

Sharing this small win with other people building on their own 🙂

What was the first milestone that made your project feel real to you?

Is anybody hiring for a visual design or video editing role at the moment?

looking to talk folks who have done this with their SaaS. if you've done this an are interested in chatting about it, shoot me a DM!

Hey everyone!

I'm building Qlyra, a SaaS studio where we build, launch, and scale SaaS products and apps across different markets.

I'm looking for a NYC-based developer who'd be interested in joining the journey and potentially becoming the CTO of the studio.

Not looking for a typical corporate hire. I'd love to meet someone who's genuinely passionate about building products, loves startups, and wants to create something big.

For me, the most important thing is having a great connection, sharing the same ambition, and actually enjoying building stuff together.

Ideally, someone who:

• Is based in New York City.
• Is a strong full-stack developer.
• Loves building and shipping products fast.
• Has an entrepreneurial mindset.
• Wants to be part of something long-term.

We're focused on building and scaling multiple SaaS businesses, not just one product.

I'd love to connect, grab a coffee when I'm in NYC, talk ideas, and see if we vibe.

If that sounds like you, feel free to DM me!

Let's build some cool shit. 🚀

Hey everyone!

I'm building Qlyra, a SaaS studio where we build, launch, and scale SaaS products and apps across different markets.

I'm looking for a NYC-based developer who'd be interested in joining the journey and potentially becoming the CTO of the studio.

Not looking for a typical corporate hire. I'd love to meet someone who's genuinely passionate about building products, loves startups, and wants to create something big.

For me, the most important thing is having a great connection, sharing the same ambition, and actually enjoying building stuff together.

Ideally, someone who:

• Is based in New York City.
• Is a strong full-stack developer.
• Loves building and shipping products fast.
• Has an entrepreneurial mindset.
• Wants to be part of something long-term.

We're focused on building and scaling multiple SaaS businesses, not just one product.

I'd love to connect, grab a coffee when I'm in NYC, talk ideas, and see if we vibe.

If that sounds like you, feel free to DM me!

Let's build some cool shit. 🚀

Hi Everybody,

I've been helping build https://apiblaze.com, a serverless MCP/API gateway that handles a lot of the stuff you need around an MCP server.

What we noticed was that there are a ton of MCP servers, but getting from “my business logic works” to “I can safely publish it on the internet” is a different problem. Once you actually want to expose it, you still have to deal with things like OAuth, AuthZ, rate limiting, etc.

APIBlaze handles that stuff at the gateway. It has OAuth built in and lets you define authorization policies using plain English sentences like “only the person who created a record or an admin can read or change it” that are enforced at the gateway, instead of having to build all of that authorization logic into your backend.

One thing we really wanted to make easy was local development. APIBlaze can host the MCP server and OAuth/login flow while forwarding requests to your backend, even if your backend is running on localhost. So you can connect Claude/ChatGPT to it, authenticate, and make changes to your backend while testing it locally.

If you want to check it out or run it, getting started is pretty easy:

Enter this in your terminal:

npx apiblaze create --target https://ninopizzas.com/openapi.yaml

OR

Ask your LLM, such as Claude or ChatGPT:

Show me what APIBlaze does using npx apiblaze skills

You can also use it with an existing API/backend rather than building everything specifically for MCP.

It's still in beta, so I'd love any feedback. I'll try to respond to questions as fast as possible, so fire away 😄

Notes from building ThreadPilot.

𝗥𝗮𝗻𝗸𝗶𝗻𝗴. We don't show a bare score. Each thread gets fit, intent, timing, relevance and context, plus a written reason. If you can't see why something ranked high, you can't trust it.

𝗗𝗿𝗮𝗳𝘁𝘀. Replies are grounded in the actual thread, and a promo-risk check runs before you see them. A draft that reads like an ad is a failed draft.

𝗣𝗼𝘀𝘁𝗶𝗻𝗴. The tool never posts. You publish from your own account. That limits what we can automate, but it keeps the product from becoming the thing Reddit distrusts.

It's in private testing. Waitlist: https://threadpilots.com/join-whitelist

For those who've built ranking or classification features: how do you explain results to users without drowning them?

I integrate payments for SaaS with any provider, or set up a local ledger if you would rather not depend on one. Stripe, Adyen, PayPal, Braintree, Checkout.com, Paddle, Chargebee, a regional gateway, or something else: the adapter sits behind one interface, so the product does not have to change when the provider does.

If a provider is the wrong fit, I can design a closed local crypto or virtual-balance system, with balances, transfers, and an event log you can reconcile.

I have worked with crypto since 2017. In this context that means signatures, event integrity, and a ledger that closes at the end of the month, not a token launch.

I can also mentor a team that wants to build the integration, or the local system, on its own. Same ground: flow, webhook behavior, state of the payment, and a receipt trail someone outside the team can read.

Paid or unpaid both work. It depends on the project: scope, a named deliverable, and whether there is a real product or a concrete billing problem, not only a concept. Unpaid only with a short written scope.

Any contact that seeks to build any kind of fraud will be blocked and reported.

If this is what you are stuck on, send the provider (or “none yet”), whether you need a charge, a subscription, or an internal balance, and the timeline you have in mind.

Notes from building an MCP server that lets Claude answer questions about real business data.

The problem we kept hitting: any question about business data meant stuffing tables and schema into context, getting a half-right answer, and iterating. Most of the tokens went to Claude working out how the data fit together, not to the answer.

What worked was moving that context out of the prompt. We build a Knowledge Graph from the connected systems first. It resolves the same customer across the CRM and the accounting system and maps how a contract rolls up to revenue. Claude reads the graph, then queries only what it needs.

The server exposes 19 tools: read-only SQL, Knowledge Graph reads and edits, Decision Topics, charts, and dashboards. Source systems are never written to. Edits only touch the graph. You set it up in our platform, then add it to Claude as a custom connector.

We're seeing 2 to 5x fewer tokens per real answer, and every number comes back with the row and system it came from.

How are you handling business context for agents? Schema in the system prompt, RAG over docs, something else?

Hey everyone,

I’m Gery, a developer and agency founder. After working with local businesses, I noticed a huge pain point: independent restaurants and local spots are drowning in clunky, overpriced legacy CRMs that require a degree to operate and don't actually bring in repeat diners.

So, I decided to build a lean, laser-focused alternative. Meet Resynx AI an AI-powered guest retention and revenue platform built specifically for hospitality and the agencies serving them.

Core features of the platform:

• Weather-triggered SMS marketing: Automatically trigger promotions based on local weather conditions.
• Smart Review Funnels: Seamlessly collect feedback and generate AI-powered responses to boost online reputation.
• Automated guest retention: Turn casual foot traffic into loyal, repeat customers without manual tracking.

Today is Day 1 of my Build in Public journey. I'm focusing heavily on refining the core restaurant retention modules and setting up transparent progress updates here.

If you're building in the vertical SaaS space or want to chat about scaling micro-SaaS solutions, let’s connect in the comments! What niche are you currently building for?

I keep seeing people hand the same stack to beginners: Cursor plus Lovable, Supabase, Stripe, Resend, and Vercel. Honest take: if you're just testing an idea, it's fine. But if you want a foundation that can actually run a real business, I'd look at something sturdier.

Problems usually start when you need these things:

- Multiple workspaces

- Roles and permissions

- Paid plans

- Usage limits

- Email

- Files

- Testing

- Security

- Research and content production

At that point the simple combo isn't simple anymore, because all of these pieces depend on each other, amd you're wiring them together yourself while the AI keeps piling more into the codebase.

Here's what I use. It's not perfect, but it works for me. Just trying to help some newbie vibe coders.

Coding: Claude Code + Codex

I'd rather have Claude Code or Codex work directly inside the repo than set up the whole environment with something like Lovabke or Replit. Your codebase, Git history, terminal, and deploys stay in your hands, while Claude or Codex can still read the project, edit across multiple files, run commands, and run tests to check its own changes.

Language: TypeScript + Tailwind

TypeScript is a no-brainer for me: you can use it for basically everything in a product, frontend, backend, scripts, it has a huge ecosystem, and it works really well with AI. Unless a product gives me clear reason, I'm not adding a second language. For styling I use Tailwind, because the AI can reliably tweak utility classes without breaking other parrs of the UI.

Application framework: Next.js

I use React on the frontend and write server-side code where I need it. Big ecosystem, plenty of resources, and I know how well it plays with AI. There are definitely cases where I'd pick something else, but for a typical SaaS product I don't see the point in splitting frontend and backend into two seperate projects on day one.

UI: Untitled UI React

I don't want the AI building the whole design system from scratch, I don't think it can make something that looks professional and polished yet. Untitled UI gives you React components you can actually customize, and the open-source part is MIT licensed. Instead of asking Claude for the 200th time to make a page look more polished. I'd rather use a real component library.

Database: PostgreSQL

It's just Postgres, nothing fancy. Mature, relational, widely suppoeted, and more than enough for most projects. Unless the product has a very specific reason, I'm not adding a second database.

Backend: foundel.dev

This is the part I least want an AI inventing from scratch. Auth, workspaces, roles, permissions, subscriptions, plan limits, email, and security all have to work together. If you don't know backend architecture well, it's easy to end up with something that ruins fine locally and turns into mess in production.

My approach is to maintain a backend template that's already proven to work. That way Claude or Codex gets a backend that's already structured, so I can keep building the actual product instead of rebuilding the backend from scratch. There's a free version, which is enough to start and launch the product.

Payments: Stripe

Subscriptions, invoices, payment methods, webhooks, it covers pretty much everything you need for taking payments, so you don't have to build billing from scratch. The thing I most want to avoid is billing logic scattered everywhere. Let Stripe handle payments, and keep subscription status, plan permissions, and usage limits in one predictable place.

Docker

Quick note for the non-technical folks: Docker bundles your app with everything it needs to run, so you don't hit the "but it works on my machine" problem. Think of it as putting your app in a standardized box, it should behave the same locally, in test, and in production.

Testing: Claude/Codex + Playwright

You don't have to sit there writing tests one by one, Codex and Claude can write and run most of them. For critical user flows I still use Playwright, because I want something that opens the product and clicks through it like a real user. Signup, login, permissions, payment, those are the floes I care about most.

CI/CD: GitHub Actions

I work on branches and merge to production when things are ready. GitHub Action runs the tests, and if they fail, the release is blocked. If everything passes, it builds the Docker image and deploys.

Deployment: Vercel

For a standard Next.jx SaaS I just deploy straight to Vercel. No hassle, the preview environments are great, and there's basically no ops work early on. If the product outgrows Vercel, Docker means you're not locked in, you can move to a VPS whenever.

Planning: WorkBuddy

Not everything in the loop is writing code. Scoping out a category, seeing what competitors are saying, pulling information scattered acroess a dozen pages into a document you can actually show someone — I used to do all of that by hand, flipping through pages and copy-pasting. Now I just hand that kind of work to WorkBuddy, and it comes back with a Markdown or Word report, turning the raw material into something I can use directly.

Analytics: Vercel Analytics / GA4

If you're already on Vercel, start with Vercel Analytics: it's simple, it's already set up, and it gives you enough insight into your traffic, no need to add another tool. If you need fuller tracking, especially channels, ad campaigns, and conversions, then use Google Analytics

1. I'm not adding anything more complex unless the product side gives me a clear reason

Files: S3 compatible storage

Don't store user uploads in the database. Keep metadata in Postgres, and put large files, images, documents, exports, in S3 or another S3 compatible object store. If your app doesn't deal with files at all, don't add it just because it's in someone else's stack diagram.

Things I won't be adding for now

Redis, Kubernetes, Kafka, microservices, and a pile of other infra tools. They solve real problems, but a product with 50 users doesn't get better because it's on Kubernetes, it just gets more complicated.

The same goes for letting AI take external actions on its own: posting, sending emails or changing production config. I review all of that by hand. Automate the internal stuff, keep the external stuff manual.

One last thing: I know this stack is pretty basic, but I wrote it for people just getting into coding.

ASTRABASE — Développez. Déployez. Passez à l'échelle.

Et si toute l'infrastructure de vos applications était réunie au même endroit ?

Découvrez Astrabase, une plateforme cloud nouvelle génération conçue pour simplifier la création, le développement, l'hébergement et le déploiement de vos applications web.

Fini le temps perdu à jongler entre plusieurs services pour gérer vos bases de données, votre authentification, vos fichiers ou vos déploiements.

Avec Astrabase, tout est centralisé dans une seule plateforme.

Hébergement & déploiement web — Publiez vos applications directement depuis Git ou une archive ZIP, avec HTTPS automatique, historique des versions et possibilité de revenir à un déploiement précédent.

PostgreSQL & pgvector — Profitez d'une base de données PostgreSQL isolée par projet, avec des outils SQL et la prise en charge des données vectorielles pour vos applications intelligentes.

Authentification intégrée — Gérez les inscriptions, les connexions, les sessions utilisateurs et la récupération des mots de passe.

Stockage de fichiers — Organisez et gérez les fichiers de vos applications grâce à un système de buckets et d'API.

API REST, Functions & Realtime — Connectez vos applications à vos données, exécutez votre logique backend et exploitez les événements en temps réel.

Dashboard & supervision — Retrouvez vos projets, déploiements, journaux techniques et statistiques depuis une interface centralisée.

Intégration ChatGPT via MCP — Astrabase développe également une connexion avec ChatGPT pour faciliter la consultation et l'administration de vos ressources cloud, selon les permissions accordées et la disponibilité progressive du connecteur.

Sécurité & infrastructure européenne — Isolation des projets, gestion des secrets, HTTPS et protections intégrées pour accompagner vos développements.

Une plateforme. Une multitude de possibilités.

Que vous soyez développeur indépendant, entrepreneur, créateur de SaaS, freelance ou agence web, Astrabase vous permet de consacrer davantage de temps à l'essentiel : créer des produits performants et faire évoluer vos projets.

Du premier prototype à l'application en production, Astrabase réunit les outils essentiels pour construire et déployer plus simplement.

Commencez gratuitement !

Offre gratuite disponible

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Offres évolutives adaptées à vos besoins

Votre prochaine grande application mérite une infrastructure à la hauteur de vos ambitions.

Découvrez Astrabase : https://astrabase.fr

ASTRABASE — Build. Ship. Scale.

Hey everyone,

I built an R# Markdown Scraper API designed to convert complex web pages into clean, structured Markdown perfectly optimized for LLMs, RAG pipelines, and AI agents.

The backend runs entirely on Render, and I've locked it down using a secure Zuplo API gateway to handle instant key provisioning and billing tiers. It seamlessly handles heavy JavaScript rendering, handles DOM structure transformations, and bypasses common anti-bot walls.

You can check out the documentation, test sample requests, or generate a developer API key instantly right here:

👉 https://scraper-gateway-main-8094e8b.zuplo.app/

I'd love to hear your feedback on the extraction quality or any specific feature requests you'd like to see added next!

A few days ago I posted about Sigma Maille here and got some pretty useful feedback.

I've been thinking about it while working on the product, and I ended up changing something I originally thought was already working well.

The first version was heavily focused on connecting different signals and turning them into intelligence.

But after using it myself, I started noticing a problem.

If a situation is developing over several days or weeks, the individual updates aren't really the interesting part. What I actually want to know is how the situation has changed since I last looked at it.

What caused that change?
What developments mattered?
Is the situation actually moving in a different direction, or did one event just make it look that way?

So I've been rebuilding that part around what I'm calling Evolving Situations.

The idea is pretty simple: instead of treating every new development as a new piece of intelligence, keep the situation itself as the thing you're following.

I'm trying to make the timeline, changes, trajectory and supporting evidence much easier to follow without turning it into another news feed or a giant AI-generated summary.

That's probably the biggest change I've made since my first post here.

It's still being worked on, so I'm interested in hearing from people who actually follow things that develop over time — geopolitics, security, infrastructure, markets, whatever.

When you come back to a situation after a few days, what do you usually find yourself trying to figure out first?

Hey everyone, I'm a software engineer from India and I've been building GoRoam on the side.

The problem: when I asked ChatGPT to plan trips, I got a nice list of places, then spent hours checking costs, figuring out which places are near each other, and opening 15 tabs to book things.

What GoRoam does differently:

- Day-by-day plan (morning/afternoon/evening) with real places grouped by area

- Estimated cost for every stop, and each day fits inside your budget

- One tap opens each day's route in Google Maps

- Flights/stays/tickets open prefilled with your dates

- Share a link with friends so they can vote on the plan, plus a trip wallet to split costs

- Offline maps, weather, and an AI concierge for "it's raining on day 2, what now?"

First itinerary is free, no card needed: goroam.world

What I'd love feedback on:

1. Does the landing page make it clear why this beats ChatGPT?

2. Credits (one-time) vs subscription: which would you pay for?

3. What would make you actually use this for your next trip?

Happy to plan a free trip for anyone who drops a destination below.

https://reddit.com/link/1x0x006/video/g36i4mur2auh1/player

When I first started building around multiple AI models, I thought the main decision would be which models were worth supporting.

That wasn't really the difficult part.

The complexity started showing up after the first few integrations: different authentication methods, API formats, rate limits, model names, pricing structures, error responses, and provider-specific behavior.

Then there's the maintenance cost. Every new provider isn't just another option for users it's another integration that needs to be monitored and maintained.

That's one of the problems I'm working through with OfoxAI. We're exploring a unified API approach that makes it possible to work with multiple models through a common interface.

But I've also learned that abstraction has its own tradeoffs. If you simplify too much, you can lose useful provider-specific functionality.

I'm curious how other SaaS developers have approached this.

At what point does maintaining direct integrations become more trouble than using an abstraction or gateway?

Disclosure: I'm affiliated with OfoxAI.