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Comms / Collaboration

Luma AI Integration

Connect Luma to BeforeQuery for grounded AI answers and agent actions across Comms / Collaboration.

Connect Luma
What is it?

About Luma

Luma is one of the Comms / Collaboration platforms BeforeQuery connects to. Once linked, the platform's data becomes a first-class source for grounded AI answers and a target for policy-gated agent actions — the same identity, approval, and audit-log guarantees every other integration ships with.

Setup

How to connect Luma

  1. Step 01

    In the BeforeQuery dashboard, go to Integrations → Comms / Collaboration and select Luma.

  2. Step 02

    Sign in to Luma with an account that has permissions to grant BeforeQuery the Comms / Collaboration scopes required.

  3. Step 03

    Confirm the connection. Luma is now available as a source and action target for every playbook in your workspace.

Explore

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How BeforeQuery uses Luma

What the agent does with your Luma connection

  • 01

    Deliver AI answers inside Luma — no context switching to a separate tool.

  • 02

    Read + respond to Luma messages via bots, DMs, or channel mentions.

  • 03

    Trigger playbooks from Luma events — slash commands, buttons, or specific phrases.

  • 04

    Send targeted, personalized notifications from any playbook into Luma.

Use cases

What teams actually do with the Luma integration

In-channel AI assistant

Employees @mention the BeforeQuery bot in Luma and get grounded answers from your knowledge base right in the thread. Cited sources are one click away. Zero context switching.

Slash-command playbook launcher

Custom slash commands (or Luma-native equivalents) trigger any playbook: /pto to file a leave request, /order-laptop to order hardware, /grant-access to request JIT access. Playbook drives the conversation.

Targeted announcements

A playbook drafts a message, targets it to the right Luma channel or user segment (role, team, tenure), and sends. Recipients get relevant messages; noise stays low.

Answer questions grounded in Luma

Employees and customers ask Luma-related questions in Slack, Teams, or the widget — BeforeQuery answers with the exact Luma record shown alongside the response. No context switching, no "log into Comms / Collaboration to check" round-trips.

Luma — Frequently Asked Questions

Common questions about connecting BeforeQuery to Luma.

No. The bot only reads messages it's directly addressed in (DMs, @mentions, replies to its own messages). Ambient channel traffic is invisible unless a playbook is explicitly configured to watch a channel.
Yes. Per-channel and per-workspace scoping is standard. Enterprise Grid customers can scope to specific enterprise-level workspaces or teams.
Standard OAuth 2.0 where Luma supports it, otherwise API-key or bearer-token auth. Credentials are stored encrypted at rest (AES-256-GCM) per workspace, never shared across customers, and rotated on request. The connection is scoped to the least-privilege set of scopes each playbook needs — you approve the scope list on install.
No. Your Luma data feeds only your workspace's own agents and answers. Nothing is used to train a shared model, and nothing crosses workspace boundaries. Bring-your-own-model is available on Enterprise if you want to pin inference to your own OpenAI / Anthropic / self-hosted deployment.
Yes. Every Luma integration is scoped at install time — you pick which resources, users, or record types are visible. You can further restrict per-playbook: a single playbook only touches the specific Luma objects it needs. Scope changes take effect on the next sync.
Every write is logged with the acting user, the playbook that fired it, the exact operation, the target entity IDs, and the timestamp — all in the immutable audit log. Writes are rehearsable in simulation mode against a copy of live data before they touch Luma for real.

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