FAQ
Do I need a GPU?
Section titled “Do I need a GPU?”No. All ML in Alcoves is CPU-only by design — face/object detection, audio tagging, and speech transcription all run on CPU. Models are selected for that constraint. See Privacy & local AI.
Is any of my data sent anywhere?
Section titled “Is any of my data sent anywhere?”No. There is no telemetry, no analytics, and no inference that leaves your instance. The Go backend is a pure API that never phones home.
What hardware do I need?
Section titled “What hardware do I need?”A machine with roughly 8 GB of RAM is the practical ceiling for the CPU-only models. Storage scales with your library — use a local disk or any S3-compatible object store. A Raspberry Pi with a USB drive and a rack with an object store are both supported.
How do I deploy it?
Section titled “How do I deploy it?”With Docker and Docker Compose for a single host, or the Helm chart for Kubernetes. External PostgreSQL and Dragonfly/Redis are expected; storage is local or S3. Start with the Quickstart.
Who can administer an instance?
Section titled “Who can administer an instance?”The first registered user becomes the owner. Owner-gated surfaces include the admin panel, the job-queue dashboard, registration policy, and ML-model selection. Within libraries, the roles are owner / admin / viewer.
Is it production-ready?
Section titled “Is it production-ready?”Alcoves is alpha (0.x.y). Expect breaking changes — they ship with
migrations and changelog entries. It targets bounded, trusted instances
(1–100 users), not anonymous mass signup.
Can other tools talk to it?
Section titled “Can other tools talk to it?”Yes — Alcoves ships an MCP (Model Context Protocol) server so MCP-capable clients can browse libraries and move files over stdio or HTTP, authenticated by a personal access token.