Audio guide system for museums

No single model speaks every language well, so we don't pretend one does. Our text-to-speech runs as a triple-engine system with smart per-language routing: Chatterbox Turbo handles English at the lowest latency, Chatterbox Multilingual covers 20+ European languages, and Qwen3-TTS takes Chinese, Japanese, and Korean. The router picks the right engine per language automatically, so a curator clicks "generate" once and the backend chooses the best voice path under the hood — no model juggling, no per-language setup on the museum's side.

Raw model output isn't shippable, so we engineered the pipeline around its failure modes. Long passages are chunked before synthesis to stop the models from hallucinating or drifting on extended text, and every chunk is cleaned with audio post-processing — a noise gate and silence trimming — so the narration sounds deliberate, not machine-stitched. Then comes the part most TTS pipelines skip: verification. Every clip is fed back through Whisper in a speech-to-text round-trip, the transcription is compared against the original script, and any clip that drifts is flagged for a human to listen before it ever reaches a visitor. Generation is automated; correctness is never assumed.

All of this is our own code on serverless GPU — PyTorch models orchestrated by the backend's job queues, not a third-party TTS API we resell. The result is studio-grade narration in 20+ languages with no human voice actors, no recording booths, and no months-long localization project. A museum can populate an entire multilingual collection in the time it once took to schedule a single recording session — and every minute of audio that ships has already been checked against its script.

Museo has a lot of surfaces that all need the same source of truth: the visitor app scanning artwork, the ambassador app populating content, the self-service admin panel, and the recognition, description, and text-to-speech pipelines running on GPU servers. We built the backend on Bun and Elysia precisely because it sits in the hot path of all of them — fast enough to stay out of the way of a ~100ms recognition response, and strict enough to keep a fast-moving multi-client product honest. Drizzle ORM models the data over PostgreSQL 18, and the API is fully type-safe end to end via Eden Treaty and OpenAPI, so the Flutter clients and the Next.js panel consume the exact same contracts the server defines. When a field changes on the backend, the clients know at compile time — not in a bug report from production.

Because Museo is a SaaS platform, the hardest invariant is that no museum can ever see another museum's data. Multi-tenant isolation is enforced at the data layer: every query is scoped to its museum, so a scan, an analytics heatmap, or a content edit only ever resolves inside the right tenant's boundary. On top of that, the backend owns the cross-cutting concerns the rest of the system shouldn't reinvent — Better Auth handles accounts and sessions across Google, Apple, and OTP with bearer tokens for the apps; PostGIS powers the geolocation queries behind the visitor app's "museums nearby"; and S3 holds every photo and audio clip the platform generates. One place to authenticate, one place to locate, one place to store.

The AI is the part that can't be synchronous, and the backend is what makes that invisible. Recognizing an artwork, writing a description, translating it, and rendering studio-grade narration on GPU workers are slow, bursty, failure-prone jobs — so the backend runs them through Redis-backed BullMQ queues instead of blocking a request. It enqueues work, brokers it to the recognition, description, and TTS pipelines, tracks state, retries, and hands results back when they're ready — exactly what lets a curator click "generate" once and walk away. That same queue layer drives the content versioning system: when a prompt changes and descriptions or audio go stale, the backend knows what to regenerate and schedules it. The apps and the AI services never talk to each other directly — they talk to the brain, and the brain keeps them in sync.