I Built Finito: A Production Tracker That Actually Gets Music Producers

*I created this post for the purposes of entering the H0 Hackathon.

H0Hackathon

The Problem I Kept Ignoring

Producers always struggle to finish their tracks — drives are always

full of unfinished projects, and the reason isn't talent, it's having

no system. I understand this issue personally because I have a music

background. Every solution out there is a generic task manager

reskinned with a music emoji. None of them understand how producers

actually work.

So I built Finito to fix that. It is personally helping me finish

and track my own music progress.

What Is Finito?

Finito gives every track a visual pipeline — Idea → WIP → Mixing →

Mastering → Finished — so producers can save and track all their

projects in one place with real-time reminders so nothing goes cold.

But the pipeline is just the container. The real features are what

happen inside it.

The Features That Matter

🎛️ Real Audio Analysis

This is the best part. Upload a mix and Finito runs an actual FFT

on the audio file using the Web Audio API — entirely in the browser,

no server processing needed. It measures real low, mid, and high

frequency balance from the actual signal data, then sends those

numbers to Gemini AI for a specific mixing diagnosis.

Not guesswork. Not loudness scores. Real frequency data from your

actual mix.

// FFT runs client-side — audio never leaves the browser

const analyser = audioCtx.createAnalyser();

analyser.fftSize = 2048;

const bufferLength = analyser.frequencyBinCount;

const dataArray = new Float32Array(bufferLength);

analyser.getFloatFrequencyData(dataArray);

🤖 DAW-Aware AI

Set your DAW and every AI suggestion changes:

• 
  FL Studio → Fruity Parametric EQ 2 references


• 
  Ableton → stock device advice
  


• 
  Logic Pro → Channel EQ suggestions


• 
  Studio One → Pro EQ guidance

It feels like a producer friend who actually knows your setup — not

a generic blog post that could apply to anyone.

✅ Milestones

At the starting phase we did not have milestones, but I thought this

could be a great feature because milestones add excitement and give

immense satisfaction even when you complete just a few checkpoints.

Break tracks into checkpoints — drums done, vocals recorded, mix

approved. Check them off as you go. Progress bars update on the kanban

card. Small wins compound into finished tracks.

📧 Automated Accountability

• Untouched for 3 days? Email.
  


• Deadline approaching? Email.
  


• Mark a track Finished? AWS Lambda fires automatically via
  DynamoDB Streams and sends a congratulations email.

That moment deserves to be celebrated.

📤 Export

Imagine you have plans to travel and all your project data is on the

dashboard. Simply export everything and work offline. Download all

projects as Excel, JSON, or CSV — BPM, key, genre, DAW, milestones,

deadlines, all included.

The AWS Architecture

This is where it gets interesting. Built on the H0 stack —

Vercel + AWS.

DynamoDB — The Core Database

I ended up with three DynamoDB tables:

The projects table uses:

• 
  GSI — for status-based queries (show all WIP projects)


• 
  TTL — auto-expires abandoned projects after 180 days


• 
  DynamoDB Streams — triggers Lambda on every status change


• 
  Transactions — atomic writes across tables when marking Finished


• 
  Conditional writes — prevents duplicate entries

This isn't a demo database. This is production-grade DynamoDB usage.

S3 — Audio Storage

Producers upload audio files up to 5GB per project. The frontend

never touches AWS credentials directly:

1. App requests a presigned URL from the API


2. Browser uploads directly to S3 using that URL


3. The S3 key is stored in DynamoDB


4. Downloads use the same presigned URL pattern

Audio never passes through Vercel — it goes straight browser → S3.

Lambda + SES — Event-Driven Emails

When a producer marks a track Finished:

DynamoDB status change

→ DynamoDB Streams detects it

→ Lambda function fires

→ SES sends congratulations email

No polling. No cron. Fully event-driven.

A separate Vercel Cron job runs daily checking for:

• Projects untouched for 3+ days → reminder email


• Deadlines within 7 days → deadline alert email


• Upcoming release dates → release reminder email

IAM — Scoped Permissions

The Lambda role only has access to:

• The specific DynamoDB tables it needs


• SES send permissions

Not admin credentials. Properly scoped IAM — because that's how

it should be done.

The Challenges

1. Never used AWS before.

DynamoDB Streams and Lambda wiring took significant debugging. IAM

permissions had to be scoped exactly right — one wrong policy and

nothing fires.

2. SES sandbox mode.

Emails land in spam in sandbox mode. In production this would use a

verified domain with DKIM and SPF. This was frustrating, but I am

happy it is working — it took significant time to get it right.

3. Knowing when to stop.

Every hour on feature fourteen is an hour the first thirteen features

go unexplained. I learned this the hard way.

What I Learned

DynamoDB Streams are underused. The pattern of "data changes →

event fires → something happens" is exactly right for reactive

applications. Cleaner than polling, cleaner than webhooks.

FFT in the browser is more capable than I expected. The Web Audio

API's AnalyserNode gives you real frequency data — not just a

visualizer, actually useful for mixing diagnosis.

DAW-aware AI was the best idea I had. Generic AI advice for

producers is everywhere. Advice that knows you're on FL Studio and

references Fruity Parametric EQ 2 — that feels completely different.

What's Next

• Full auth with AWS Cognito


• Spotify and SoundCloud integration for release tracking


• Mobile app for logging ideas on the go


• Inspiration library — reference tracks, album art, DAW templates