Creating a Vertical

Binexia uses a template pattern: the same code serves every vertical. Only the semantic model configuration and seed data change. This guide covers what you need to create a new vertical.

The Template Pattern

Same codebase (Laravel + Nuxt + Agno)
  └─ Different configuration per vertical:
       ├─ Semantic model (entities, metrics, dimensions, vocabulary)
       ├─ Seed data (demo records)
       ├─ Dashboard templates (widgets, layouts)
       ├─ Goals (scheduled agent configurations)
       └─ LLM routing defaults (provider/model per agent)

Checklist

1. Domain Tables (`tenant_data` schema)

Create the business tables for your vertical. Examples:

IntelliTravel	Manufacturing	Legal
`customers`	`clients`	`clients`
`bookings`	`orders`	`cases`
`destinations`	`products`	`practice_areas`
`suppliers`	`suppliers`	`attorneys`
`contact_history`	`quality_reports`	`time_entries`

2. Semantic Entities

Map each domain table to a natural language entity with description and active_filter_sql.

3. Metrics

Define the key performance indicators:

IntelliTravel	Manufacturing	Legal
Total Bookings	Total Orders	Total Cases
Revenue	Revenue	Billable Hours
Avg Booking Value	Avg Order Value	Avg Case Value
Cancellation Rate	Defect Rate	Case Dismissal Rate
Active Customers	Active Clients	Active Clients
Repeat Booking Rate	Repeat Order Rate	Client Retention Rate

Time: booking date, travel date → order date, delivery date → case filed date, case closed date Categorical: destination, channel, segment → product line, region, priority → practice area, attorney, court

5. Vocabulary

Domain-specific business terms. This is the most important part — it's where domain expertise gets encoded:

IntelliTravel	Manufacturing	Legal
"high-value customer"	"enterprise client"	"major client"
"at-risk customer"	"churn-risk client"	"at-risk client"
"seasonal booking"	"seasonal order"	"seasonal case volume"
"supplier SLA breach"	"supplier quality issue"	"attorney response delay"

6. Goals

Configure scheduled agent goals:

{
  "name": "cancellation_rate_alert",
  "agent_type": "anomaly",
  "agent_schedule": "0 8 * * *",
  "alert_threshold": { "above": 20.0, "window_days": 7 }
}

7. Seed Data

Create a seeder class (like UbiosDemoSeeder) that populates:

Users with roles
Semantic model tables (entities, metrics, dimensions, vocabulary)
Goals
Dashboard templates with widgets
Sample agent outputs for demo purposes
LLM routing defaults

8. Test

Run the seeder
Log in and verify dashboards render correctly
Test natural language queries against the semantic model
Verify vocabulary terms trigger correctly
Check scheduled agent configurations

Example: Manufacturing Vertical

Info

The code is identical to IntelliTravel. Only the configuration below changes.

Entities: client, order, product, supplier, quality_report Key metrics: Total Orders, Revenue, Avg Order Value, Defect Rate, Active Clients, Repeat Order Rate Key dimensions: order_date, delivery_date, product_line, region, supplier Vocabulary: "enterprise client" (order value greater than $50K), "defect" (quality_score below 80), "on-time delivery" (delivery_date on or before promised_date) Goals: Defect Rate Alert (anomaly, daily), Client Churn Risk (behavioral, weekly), Monthly Revenue Forecast (forecast, monthly)