Flowdia

Build real apps with AI — not demos.
Real backend. Postgres. API. MCP. Day one.

[Flowdia @flowdia_ai]

One prompt. Two AI builders. Different output!
One built the app, the other needs a real infrastructure!
Flowdia built it, because it's the real infrastructure, the first MCP Native AI Builder. A complete AI Agile team!

Watch the video below! Give it a try at: https://t.co/7mjrMqa9Th

[Flowdia @flowdia_ai]

Before Flowdia: it shipped fast, serious bugs and security vulnerabilities hiding everywhere

After Flowdia: QA and Security agents in the loop, same build keeps getting fixed

[Flowdia @flowdia_ai]

Before, vibe coding felt like shipping,

Now, production-ready complex apps expose every shortcut

[Flowdia @flowdia_ai]

Prompt - code - good luck is not software engineering

[Flowdia @flowdia_ai]

Most AI Builders stop at the beautiful screen.
Flowdia doesn’t.

10 AI Agents plan, design, build, review and test.
Real backend.
Real database.

Preview and production environments.
Not a glued template.
A full stack application

[Flowdia @flowdia_ai]

@SydSachar exactly. process is the moat. anyone can wire a model to a deploy button. the hard part is everything that catches the broken auth, the missing edge case, the architecture decision that prevents a rewrite three months in.

[Flowdia @flowdia_ai]

Most AI app builders skip the boring parts.

UX planning.
Review.
QA.
Security.

Then people wonder why the generated app feels like a landing page with buttons.
Real full stack apps are not one prompt. They are a process!

[Flowdia @flowdia_ai]

A real AI builder can’t be one agent writing files.
It needs PM, UX, developer, reviewer, QA, security.
Basically an Agile team, not a prompt box!

[Flowdia @flowdia_ai]

AI-generated demos are a phase. The destination is AI-generated production apps. Not stuck in a CLI. Not stuck in a desktop agent. Real apps, deployed and live, anywhere they need to run.

[Flowdia @flowdia_ai]

Give flowdia a try 👉 https://t.co/JM3RUcXKCX

[Flowdia @flowdia_ai]

AI builders: connect our MCP to your Agent, so that your Agent tell our Agent to build your app 😅

Flowdia: Connect "Your" App MCP to your Agent, and let it continue building on your remote App runtime!

That's the different between Flowdia and anything else!

[Flowdia @flowdia_ai]

"AI app builders" that can't run a cron job aren't building apps. They're building landing pages.

Flowdia ships real backends, webhooks, background jobs, Postgres, hosted APIs, remote repo access... by default.

[Flowdia @flowdia_ai]

Give it a try 👉 https://t.co/JM3RUcXKCX

[Flowdia @flowdia_ai]

Most AI builders ship demos.

Flowdia ships real apps — with a real backend, Postgres, API, and MCP server. On day one.

90 seconds 👇

[Flowdia @flowdia_ai]

@GusevV1987 Yep and that's the part the category hasn't named yet. Builders give you a UI. Generators ship you a product. Different problem, different output.

[Flowdia @flowdia_ai]

Other AI app builders give you a frontend.
Flowdia gives you the whole product:
→ Frontend
→ Backend
→ Database
→ Auth
→ Deployment
→ AI integrations
One prompt. A real, shippable product — not a demo.
https://t.co/4jiPc8aBsF

[Flowdia @flowdia_ai]

Want to get the most out of your AI subscriptions ? also deploy with way less budget than ever ?

1. Initiate your project from Flowdia using a prompt.
2. Get your MCP Server URL from your project Admin panel at Flowdia.
3. Drop your MCP server at your Agent of choice (claude code, cursor ...etc)
4. Start your prompt with "You are working on a remote Repo using MCP X"

And that's it, finalize your project using any AI Agent of choice if your budget is tight!, remote runtime, you control every bit of it.

However we will always completing using our AI Agile team, structured AI Agents work is superior to a single Agent, But you have full control on what to use!

What are you waiting for ? Go give it a try: https://t.co/7mjrMq9C3J

[Flowdia @flowdia_ai]

Prompt used:

Build a media transcoding and streaming platform. Users upload raw video files in any format (MKV, AVI, MOV, MP4, WebM) and the app automatically transcodes them into HLS adaptive bitrate streams with multiple quality levels (360p, 720p, 1080p). During upload, extract the audio track separately as MP3, generate a thumbnail grid (one frame every 10 seconds), detect scene changes and create chapter markers, and extract embedded subtitles or run speech-to-text to auto-generate SRT captions. Users can browse a library of their uploaded videos, play them in a custom video player with quality switching, subtitle toggling, chapter navigation, and playback speed control. Include a dashboard showing transcoding job progress with a queue, estimated time remaining, and storage usage per user. Add a clip editor where users select a start/end time on any video, crop the frame, overlay text or a watermark image, apply a color filter, and export the clip as MP4 or GIF. Support batch uploads with drag-and-drop.

[Flowdia @flowdia_ai]

Same prompt. Two platforms. One builds a UI mockup. The other builds a working app with FFmpeg, HLS streaming, and a transcoding job queue.

The line between a prototype and a real product is runtime control. That's what we built Flowdia to solve.

Full breakdown in the video.