> ## Documentation Index
> Fetch the complete documentation index at: https://docs.switchbord.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Customization And Builder

> How user-defined attributes, segments, and a future workflow builder should evolve in this platform.

# Customization And Builder

This page summarizes how `gb-fu-charles` should approach user-driven customization and a future graphical journey builder.

## The short answer

We should borrow the **pattern** from `gbcrm` and ElevenLabs, but not copy their full platforms into this repo.

What fits:

* workspace-defined contact attributes
* normalized tags
* saved dynamic segments
* configurable inbox and contact views
* a typed graphical journey builder
* a future tool catalog and knowledge-base layer

What does not fit yet:

* full custom-object creation
* a broad CRM-style metadata engine
* a general-purpose no-code automation platform
* AI-agent complexity before the message plane is real

## Why this matters

Without a real customization model, every request for:

* new tags
* new contact properties
* new segment columns
* new inbox side-panel fields

becomes a developer task.

That is operationally slow and forces product work into engineering even when the requirement is workspace-specific.

## The recommended direction

### Phase 1: Controlled customization

Start with:

* custom contact attribute definitions
* normalized tags on contacts and conversations
* segment definitions and snapshots
* configurable contact and inbox views

### Phase 2: Typed automation schema

Before adding a canvas, define:

* a typed journey node model
* a typed condition model
* stable references to tags, segments, templates, and custom attributes
* publish-time validation rules

### Phase 3: Graphical builder ✅

Shipped (Apr 2025 sprint). Uses a dedicated React Flow graph module with a small node catalog:

* trigger
* condition
* wait
* send template
* update attribute
* add/remove tag
* outbound webhook
* AI agent step
* exit

The editor is at `/journeys/[id]` with inline validation, cycle detection, and a publish pipeline that creates immutable journey snapshots.

### Phase 4: Knowledge and tools ✅

Shipped (Apr 2025 sprint). Now that the message runtime is durable:

* knowledge assets for FAQ/policy/product facts (powered by asset storage, BORD-187)
* a controlled tool catalog (agent tool-use permissions in `ai_agents` table)
* preview and simulation tooling (phone-frame renderer in template builder, journey node validation)

## Why not copy the full `gbcrm` model?

The sibling CRM supports a much broader metadata engine:

* custom objects
* custom fields across the product
* graph overviews of the data model
* workflow builder infrastructure

That breadth is useful in a CRM. It would be too heavy here if adopted wholesale before the WhatsApp control plane is stable.

## Why ElevenLabs is still useful

The best things to borrow are UX patterns:

* template-first entry
* left-rail catalog plus center canvas
* use-template flow
* preview/testing before publish
* separate knowledge and tool catalogs

That is a better operator experience than throwing users into raw JSON or a blank node canvas.

## Recommended order

1. Custom attributes
2. Normalized tags
3. Saved segments
4. Configurable views
5. Typed journey schema
6. Graphical builder
7. Knowledge and tools

## Read next

* [Platform Architecture](/platform/architecture)
* [Feature Matrix](/platform/feature-matrix)
* [Roadmap](/roadmap)