---

name: lead-discovery description: "AI-driven lead discovery for B2B export. Searches web for potential buyers matching ICP, evaluates fit, and creates CRM records for follow-up."

Lead Discovery — AI-Powered Prospecting

Automatically search, filter, and evaluate potential buyers based on your ICP profile.

Triggers

• Cron scheduled execution (Daily 10:00)
• Manual command from owner: "Search for leads in [market/industry]"

Search Strategy

Search Dimensions (rotate daily, pick 1-2)

1. Target Market Procurement

   • "{{product}} buyers [target country] 2026"
   • "[target country] fleet expansion logistics company"
   • "[target country] construction equipment procurement"

2. Trade Shows & Procurement Signals

   • "{{product}} buyers exhibition Africa Middle East 2026"
   • "transport logistics tender [region]"

3. Company Research (read website)

   • After discovering a target company, read their website for detailed info

4. Customs / Trade Data

   • "[target country] {{product}} import statistics"
   • "{{product}} import demand [region] 2026"

Search Execution

Jina Search (find potential buyers)

curl -s 'https://s.jina.ai/QUERY_URL_ENCODED' \
  -H 'Authorization: Bearer $JINA_API_KEY' \
  -H 'Accept: application/json'

Jina Reader (read company website)

curl -s 'https://r.jina.ai/https://target-company.com' \
  -H 'Authorization: Bearer $JINA_API_KEY' \
  -H 'Accept: application/json'

JINA_API_KEY in .secrets/env. Get one free at https://jina.ai/

3-Layer Enrichment Pipeline

Layer 1: Website Extraction

Read company website via Jina Reader → extract:

• Company size, employee count
• Product lines, services
• Certifications (ISO, etc.)
• Contact info (email, phone, WhatsApp)
• Office/warehouse locations

Layer 2: Purchase Signal Search

Jina Search for:

• "[company name] procurement tender"
• "[company name] fleet expansion"
• "[company name] import export"

Layer 3: Information Integration

• Combine all findings into enrichment profile
• Calculate ICP score based on USER.md criteria
• Store research notes in Supermemory with tag "customer_research"

Evaluation Flow

For each discovered prospect:

1. Extract: company name, country, industry, size, contact info (email/WhatsApp/phone)
2. Read company website via Jina Reader for deep understanding
3. Score per USER.md ICP criteria (1-10)
4. ICP >= 5: Write to CRM (source=web_discovery, status=new)
5. ICP >= 7: Also mark as hot_lead, create research note
6. Email found: Mark next_action=email_outreach
7. WhatsApp found: Mark next_action=whatsapp_outreach

Output Format (report to owner)

Today discovered X potential leads:

1. [Company] - [Country] - ICP [X]/10
   Industry: [industry] | Size: [size]
   Source: [search query]
   Contact: [email/website/whatsapp]
   Recommendation: [Send cold email / WhatsApp contact / More research / Enter nurture pool]

Added to CRM: X | Pending email outreach: X | Pending WhatsApp: X

Search Frequency & Quota

• Max 20 searches per day (API quota management)
• Weekly coverage: Africa 2 days, Middle East 2 days, SEA 1 day, LatAm 1 day, Other 1 day
• Duplicate companies auto-skipped (check CRM first)

Search Templates by Market

Africa (Mon/Tue)

• "{{product}} importers Nigeria Lagos"
• "logistics company Tanzania fleet"
• "construction company Kenya equipment procurement"

Middle East (Wed/Thu)

• "{{product}} dealers Saudi Arabia"
• "logistics fleet UAE Dubai"
• "construction equipment Oman transport"

Southeast Asia (Fri)

• "{{product}} importers Philippines Manila"
• "logistics company Vietnam fleet"
• "construction Indonesia heavy vehicles"

Latin America (Sat)

• "{{product}} importers Brazil"
• "logistics company Chile fleet"
• "mining transport vehicles Peru"