Lead Generation

The lead generation system provides a reusable outreach pipeline that any Amble tenant can use to discover prospective business partners, enrich them with web research, and draft personalized outreach emails.

Overview

The system uses three entity types, one global agent, and configurable views to manage the full outreach lifecycle:

1. Discovery — Find companies via web search, create prospect records
2. Enrichment — Research prospects, capture details and reputation
3. Email Drafting — Generate personalized outreach using business-type templates
4. Human Review — Review drafts, approve, and send

Entity Types

Business Type

Categories of businesses to target. Each business_type entity holds:

• Description — What this type of business does
• Email templates — Subject and body templates with placeholders ({company_name}, {to_name}, {our_company}, etc.)
• Value proposition — How your services relate to their business
• Search queries — Web search templates with {city}/{state} placeholders
• Relevant services — Which of your services matter most to them

Prospect

A discovered company in the outreach pipeline. Key fields:

• business_type_name — Denormalized from connected business_type entity (enables kanban groupBy)
• service_area — Geographic area where the company operates
• outreach_status — Pipeline stage: discovered → enriched → email_drafted → email_sent → responded → converted
• enrichment_notes — AI-generated research summary
• Connection to business_type — Structured link for template lookups

Outbound Email

An AI-drafted outreach email. Key fields:

• subject/body_text — Personalized from business_type templates + prospect enrichment
• channel — email, snail_mail, or phone
• status — draft → ready → sent → opened → replied → converted
• Connection to prospect — Links email to its target

Lead Finder Agent

A global system agent (is_system: true) that works for any tenant by reading workspace context at runtime.

How It Works

1. Reads workspace agent_context to understand the business, services, geography
2. Searches for business_type entities to get target categories
3. For each category × city combination, uses webSearch to find companies
4. Creates prospect entities linked to the appropriate business_type
5. Enriches prospects with web research (enrichment_notes)
6. Drafts outbound_email entities using business_type email templates

Heartbeat Schedule

Runs weekdays at 8 AM and 1 PM ET. Focuses on enrichment and email drafting. Discovery is triggered by users via chat.

Chat Suggestions

• "Discover all prospects for every business type in our target area"
• "Enrich the next batch of discovered prospects"
• "Draft outbound emails for enriched prospects"
• "What's the current pipeline status?"

Views

Six views manage the pipeline:

Setting Up for a New Tenant

1. Create business_type entities — Define the categories of businesses to target, with email templates personalized for your business
2. Configure workspace agent_context — Add your company description, services, geography, and value propositions
3. Use Lead Finder agent — Available in chat for all tenants. Say "Discover realtors in [your city]" to start

The agent reads your workspace context and business_type entities to customize its behavior — no code changes needed.

Design Decisions

• business_type as entity type (not enum) — Extensible without code changes. Users add new categories by creating entities.
• Denormalized business_type_name — Kanban can't group by connection fields (reads entity.content only). Stored as string for groupBy, with connection for structured navigation.
• Global agent — One agent definition serves all tenants. Personalization via workspace context injected at runtime by buildAgentSystemPrompt().
• Email templates on business_type — Each category has its own outreach messaging. Agent reads templates and personalizes with prospect-specific details.

Related Modules

• Agent System — Agent runtime, heartbeat, tool resolution
• Entity System — Entity types, connections, extraction
• View System — Kanban, data tables, block-based layouts