---
title: "Hyperstate AI Case Study"
canonical: https://wavect.io/case-studies/hyperstate-ai/
language: en
description: "AI-assisted music production platform with a producer-like assistant that held context across sessions. The startup ran out of funding after launch."
image: "https://wavect.io/img/general/bak/open_graph_preview.jpg"
---

[← All case studies](/case-studies/)

![Hyperstate AI logo](/img/clients/svg/hyperstate-ai.svg)

CASE STUDIES · 2025

Hyperstate AI

# Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room.

Hyperstate AI ran an AI-assisted music production platform. Creators uploaded audio and worked with a producer-style assistant (the Louis Bell persona) that kept full context across sessions. The startup ran out of funding after launch.

[“They were on time, attentive, and easy to work with.” Jonathan Rowden Clutch](https://clutch.co/go-to-review/f2290100-9e13-4140-a1b0-0ee301a5fd39/476263)

AI Fullstack Build 2025 Wind Down

At a glance

Engagement Fullstack Build

Industry [Music Tech AI](/industries/music-audio/)

Stage Seed

Engagement size Extended retainer

Year 2025

Stack

Python / Django OpenAI API Neo4j PostgreSQL Docker

Status Wind Down

## Overview

Hyperstate AI ran an AI-assisted music production platform. Creators uploaded audio and worked with a producer-style assistant (the Louis Bell persona) that kept full context across sessions. The startup ran out of funding after launch.

## What's the challenge?

A single GPU-heavy server handled audio processing, lyrics, transcription, MIDI generation, and the producer agent. Deploys were manual. Compute cost scaled with the box rather than with usage, and the architecture had been built for a demo rather than for launch traffic. Scaling it out meant separating the workloads first.

## What call did we make?

### One server doing everything wasn't going to survive launch.

> Audio processing, lyrics, transcription, generation, all stacked on a single GPU box, deployed by hand. It carried the demo and folded under real load. We split it into focused services with clean responsibility boundaries, dockerised every component, and swapped the heaviest in-house libraries for lightweight, scalable hosted alternatives. Same product surface, fraction of the compute bill, deploys nobody has to babysit.

## What We Did

Drove the transition of GPU-heavy integrations out of the monolithic single-server setup into a distributed, microservice-oriented backend with clearly separated responsibilities (agents, audio processing, and generation services), each with its own scaling envelope. Drove the modernisation of the deployment stack from manual deploys to a dockerised, orchestrated infrastructure across every component. Drove the migration from local, self-managed, compute-heavy audio, lyrics, and transcription libraries to lightweight, scalable alternatives, cutting latency and the compute bill at the same time. On top of that: Django REST API, authentication, project and sample management, MIDI generation workflows, Neo4j knowledge graph, PostgreSQL. Same product surface, infrastructure that carries growth instead of fighting it.

## Outcomes

### GPU Monolith - → Microservices

### Latency & Cost - Both Down

Want outcomes like these on your build?

Fixed scope. Fixed deadline. Signed SoW.

[Get in touch](/contact/)

## Selected Screens

![Hyperstate AI, screen 1](/img/case-studies/hyperstate-ai/001_hu_e5585f73b14b7ebf.webp)

![Hyperstate AI, screen 4](/img/case-studies/hyperstate-ai/004_hu_7155b9a087fd7e89.webp)

![Hyperstate AI, screen 5](/img/case-studies/hyperstate-ai/005_hu_6df59b41ac9d3bf.webp)

![Hyperstate AI, screen 7](/img/case-studies/hyperstate-ai/007_hu_d33a04e985abd60b.webp)

![Hyperstate AI, screen 8](/img/case-studies/hyperstate-ai/008_hu_5c0f02666f94b076.webp)

![Hyperstate AI, screen 9](/img/case-studies/hyperstate-ai/009_hu_f95c47bf1a90bd7e.webp)

![Hyperstate AI, screen 10](/img/case-studies/hyperstate-ai/010_hu_528bd9209bab2ea1.webp)

## Client Voice

[Clutch · Verified](https://clutch.co/go-to-review/f2290100-9e13-4140-a1b0-0ee301a5fd39/476263)

> **They were on time, attentive, and easy to work with.**

Wavect GmbH has helped the client pitch their product to investors and end customers. The team is punctual, attentive, and easy to work with. Moreover, the client is impressed with the vendor's expertise in the niche area of knowledge engineering.

Jonathan Rowden CEO, Twinsoft, Inc.

Want to have the same impact?

Fixed scope. Fixed deadline. Signed SoW.

[Get in touch](/contact/)

## What We Learned

Heavy ML work doesn’t belong in your web request path. The moment audio, lyrics, and transcription each pull a model into the same box, every load spike takes the whole product down with it. The win is boring infrastructure: separate services for separate compute profiles, orchestrated deploys, hosted alternatives for the libraries you have no business owning.

## Tech Stack

- [Python / Django](https://www.djangoproject.com/)
- [OpenAI API](https://openai.com/)
- [Neo4j](https://neo4j.com/)
- [PostgreSQL](https://www.postgresql.org/)
- [Docker](https://www.docker.com/)

## Tags

- AI
- Music Tech
- Audio

Related services

- [AI Agents & Products](/services/artificial-intelligence/)
- [Custom Software Development](/services/software-development/)

Client references and trademarks

Wavect publishes these case studies about its own work. Client names, logos and trademarks are the property of their respective owners and are used here to identify the work, not to imply any partnership, sponsorship or endorsement. Each case study describes Wavect's own contribution inside a larger effort, and other parties, including the client's own teams and other vendors, contributed to the results. Figures attributed to a client are that client's own reported numbers. Figures about our work come from our records as of the review date, and we provide evidence on request. Reviews are reproduced from the platform named on each card and link to their source. We do not publish the commercial terms of any engagement, and product screenshots remain the property of the client shown. If you are named here and want a correction, a change or a removal, write to us and we will act on it: [office@wavect.io](mailto:office@wavect.io)

### [PromptID](/case-studies/promptid/)

PromptID is an AI-native EdTech platform for employers and universities. It examines learners by analysing the train of thought, not by rewarding memorisation. …

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