D
Support / Contact Center

Dixa AI Integration

Connect Dixa to BeforeQuery for grounded AI answers and agent actions across Support / Contact Center.

Connect Dixa
What is it?

About Dixa

Dixa is one of the Support / Contact Center 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 Dixa

  1. Step 01

    In the BeforeQuery dashboard, go to Integrations → Support / Contact Center and select Dixa.

  2. Step 02

    Sign in to Dixa with an account that has permissions to grant BeforeQuery the Support / Contact Center scopes required.

  3. Step 03

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

Explore

Related integrations

3
3CX

3CX is one of BeforeQuery's Support / Contact Center integrations. Connect it once and every agent in your workspace can read, reason over, and act on 3CX data with your policies + audit trail.

8
8×8

8×8 is one of BeforeQuery's Support / Contact Center integrations. Connect it once and every agent in your workspace can read, reason over, and act on 8×8 data with your policies + audit trail.

A
Aircall

Aircall is one of BeforeQuery's Support / Contact Center integrations. Connect it once and every agent in your workspace can read, reason over, and act on Aircall data with your policies + audit trail.

How BeforeQuery uses Dixa

What the agent does with your Dixa connection

  • 01

    Read Dixa conversations to give agents customer context across every past interaction.

  • 02

    Draft cited AI replies inline in the Dixa composer — every draft grounded in your macros + knowledge base.

  • 03

    Auto-triage and route inbound Dixa conversations based on intent, sentiment, or product area.

  • 04

    Deflect known-answer conversations before they reach a human, with your policies deciding the confidence threshold.

Use cases

What teams actually do with the Dixa integration

AI drafts in the Dixa composer

Support agents write replies with an AI-drafted first pass grounded in your help center, past tickets, and product docs. Every claim carries a citation an agent can click to verify. Median reply time drops 40-60% without sacrificing quality.

Confidence-gated deflection

Inbound Dixa conversations that look like a "how do I" question with a known answer get an AI reply grounded in your KB. Confidence over 0.85 posts the reply; below, it queues for a human with the draft attached.

Ticket triage and routing

New Dixa conversations get intent-classified, sentiment-scored, and routed to the correct team — Billing, Onboarding, Bug, Feature Request — before the queue sees them. Reduces mis-routes 70%+.

Answer questions grounded in Dixa

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

Dixa — Frequently Asked Questions

Common questions about connecting BeforeQuery to Dixa.

Only what the playbook needs. PII detection runs on inbound content before it reaches the LLM — emails, phone numbers, credit-card fragments are redacted before retrieval and re-inserted only in the outbound reply where policy allows. Full PII controls at the workspace + playbook level.
Yes. Simulation mode replays a past Dixa conversation through the playbook, shows what would have been drafted or posted, and compares to what the human agent actually did. Ship changes with data, not hope.
Standard OAuth 2.0 where Dixa 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 Dixa 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 Dixa 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 Dixa 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 Dixa for real.

Ready to connect Dixa?

Start free. No credit card required. Connect your first integration in under 5 minutes.

Get started free