What gets installed and where data goes

Docker Compose starts eight services. These include the website, services that handle requests and AI connections, two background workers, and three storage services.

Where files and records live

Postgres stores records such as matters, chats, citations, skills, playbooks and the audit log. RustFS — the S3-compatible object store that replaced a bundled MinIO (ADR 0036) — stores uploaded files; .env files that still set MINIO_* variables keep working, since docker-compose.yml falls back to them when the newer OBJECT_STORE_* variables aren’t set. Redis holds the ingest and background-job queues the two workers consume from, plus other working data (docker-compose.yml). The anonymization layer’s pseudonym mapping lives in the gateway process’s own memory and is never persisted. A recovery plan needs to account for all of these together.

For the full accounting, including what leaves your environment, see the trust centre’s data-boundary page. The shape of it:

Accounts, chat history, citations, skills, playbooks, audit log

Where

PostgreSQL

Leaves your environment?

No

Uploaded files

Where

RustFS (S3-compatible)

Leaves your environment?

No

Anonymization pseudonym mapping

Where

Gateway process memory only, never persisted

Leaves your environment?

No

Inference request payload

Where

Travels through the Inference Gateway to the configured provider

Leaves your environment?

Yes, per the routed Inference Tier

(docs/architecture.md, “Where data lives, in detail”)

What may use the internet

Installation may download software and models. A cloud AI service receives the text needed to answer a question — the inference request travels through the Inference Gateway to whichever provider is configured. Which tier it routes at, from air-gapped local (Tier 1) to a consumer or free-tier endpoint (Tier 5), is the operator’s own configuration choice. It’s shown on each assistant message that carries a routed tier, and recorded in the audit log (README.md, “Inference Tier Awareness”; docs/architecture.md).

Document search may also send text to a service that prepares it for meaning-based searches. Beyond inference, the Inference Gateway is also the only path for tool calls — case-law and other research-source lookups, and any operator-approved MCP connector. Those are opt-in and off by default: nothing leaves for a tool call until an operator explicitly enables a tool_providers entry (docs/HONEST-STATE.md §5.5). Two more paths are off by default and have their own settings: optional SMTP email for Autonomous Layer notifications (smtp_host, unset by default; api/app/config.py:418) and OpenTelemetry export (OTEL_EXPORTER_OTLP_ENDPOINT, unset by default; docs/architecture.md:204). Neither is the slack-bridge / teams-bridge integration bridges named below under “Optional services” — there is no email or monitoring bridge service.

No data reaches LegalQuants by default; the deployment emits no telemetry unless you opt in, and what you opt into carries no content (docs/architecture.md).

Professional duty

Choosing a tier is a confidentiality decision, not only a configuration one — it decides whether a client’s material reaches a third party and on what retention terms. Duties differ by jurisdiction and by engagement; check your own rules and any client outside-counsel or vendor terms. Projects marked privileged: true force a minimum tier and mark every chat and audit entry privileged (README.md, “Projects”), and minimum_inference_tier on a project or skill makes the gateway refuse weaker routing with HTTP 403 tier_below_minimum.

Who can connect by default

The default service ports accept connections from the computer running Docker, not other computers on the network: each binds to ${*_BIND_ADDR:-127.0.0.1} by default (docker-compose.yml). Check the settings before making the app available more widely. Monitoring is a related but wider story — the api’s and gateway’s Prometheus /metrics endpoints are always on and unauthenticated. With the default Compose bindings they’re reachable from the Docker host’s own loopback interface and from any other container on the Compose network; reaching them from anywhere else needs the operator to rebind the port or route through a reverse proxy (docs/observability.md, “No telemetry by default”).

Before you install

Have Git and Docker Desktop 4.x+ (or Docker Engine 24+ on Linux) with Compose available. The source install builds its own images; you do not need Python or Node installed on the host. The README suggests roughly 8 GB of free disk and 6 GB of memory available to Docker (README.md, “Quick Start”) — these are planning figures, not a measured capacity guarantee; downloads, build files, documents and local models need more room. Named reference configurations for how much a laptop, a small server, or an air-gapped local-inference host can actually carry are on the hardware sizing page.

Provider API keys (Anthropic, OpenAI, etc.) are optional at install time; the stack starts without one and inference calls return “no provider configured” until you add at least one.

Services and default ports

The eight default services are web, api, gateway, ingest-worker, arq-worker, postgres, redis and rustfs (docker-compose.yml). The website uses host port 3000, the API 8000 and gateway 8001. Postgres uses 5432, Redis 6379, and RustFS 9000 for file access and 9001 for its console:

WEB_HOST_PORT=3000
API_HOST_PORT=8000
GATEWAY_HOST_PORT=8001
POSTGRES_HOST_PORT=5432
REDIS_HOST_PORT=6379
OBJECT_STORE_API_HOST_PORT=9000
OBJECT_STORE_CONSOLE_HOST_PORT=9001

Each can be changed through its corresponding *_HOST_PORT setting in .env. POSTGRES_HOST_PORT is the one that most often collides, typically with a Homebrew Postgres on macOS (README.md “Troubleshooting”).

The stack also refuses to start until four secrets are set in .env — POSTGRES_PASSWORD, OBJECT_STORE_SECRET_KEY (accepted under its legacy name MINIO_ROOT_PASSWORD too), LQ_AI_GATEWAY_KEY, JWT_SECRET — each any long random string (README.md “Quick Start”).

Optional services

The local Compose profile (--profile local) adds ollama, for fully local inference. The slack and teams profiles (--profile slack, --profile teams) add the corresponding bridges; enabling a profile does not prove the outside service connection works. Those connections need their own setup and testing.

Replacing identifying details has limits

The optional anonymization feature can miss names and other identifying details. A log saying it ran is not proof that all sensitive information was removed. It is off by default in the example settings (gateway.yaml.example). Choose a model and connection suitable for the full text that could be sent, including document passages used to answer the question.

Silent failure

A missed entity is silent. The Anonymization Layer’s recall on legal prose is empirically unmeasured (README.md, “Honest validation posture”; docs/security/anonymization.md §“What’s validated vs what’s unvalidated”). What you can observe instead: the audit row’s anonymization_applied flag tells you the middleware ran, not that it caught everything. For matters where that residual risk is unacceptable, route at Tier 1 (local Ollama).

Next

• Set up LQ.AI and try your first document