Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room.
AI Development
Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room. - View 1
Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room. - View 2
Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room. - View 3
Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room. - View 4
Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room. - View 5
Broke up the GPU monolith. Lower latency, lower bill, deploys that don't need a war room. - View 6
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.
What was the main challenge in this project?
A single GPU-heavy server handled audio processing, lyrics, transcription, MIDI generation, and the producer agent. Deploys were manual. The compute bill grew faster than usage. The architecture carried a demo but couldn’t carry the launch. No horizontal scaling, no failure isolation, one bad deploy took the whole product offline.
What was the outcome or impact for the client?
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, thirdweb-linked JWT auth, project and sample management, MIDI generation workflows, Neo4j knowledge graph, PostgreSQL. Same product surface, infrastructure that carries growth instead of fighting it.

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Project Details

W
Posted by
Wavect GmbH
Jun 3, 2026
Industry:Media & Entertainment
Budget:$50,000 - $100,000
Duration:6 - 12 months
Project URL
LangChainTypeScriptReactPythonDjangoNeo4jPostgreSQLDockerOpenAIChatGPT

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