Outreach Intelligence — Hyper-Personalized Briefs & Sequences

Stop sending generic spam. Start sending high-converting, signal-driven outreach.

Outreach Intelligence generates hyper-personalized outreach strategies, multi-channel messaging briefs, and sequence copy for every prospect. Powered by Laya System-1 Decision Intelligence, it dynamically weaves together target pain points, hiring signals, buying intent triggers, and mutual connection angles into cold emails, LinkedIn notes, and phone call openers.

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Core Question Answered:

How should I reach out to convert this prospect?

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Key Capabilities

• Multi-Channel Copy Generation:
  • Cold Email: Signal-hook subject lines, pain-point body copy, tailored value proposition, and low-friction call-to-action (CTA).
  • LinkedIn Sequence: 300-character connection request note + high-context follow-up message.
  • Cold Call Script: Pattern-interrupt opener, contextual hook mentioning verified company triggers, and qualification question.
• Decision Engine Prioritization:
  • Outreach Priority Score (0–100): Evaluates intent signals, referral warmth, and prospect authority to tell you who to message first.
  • Personalization Strength (0–100): Scores how specifically tailored the messaging is vs. generic templates.
  • Actionability & Timing Urgency: Flags whether the lead is ready for immediate outreach or scheduled follow-up.
• Native Pipeline Chaining:
  • Ingests datasets seamlessly from AI Prospect Intelligence, Buying Intent Finder, Hiring Signal Finder, or Business Opportunity Finder via Apify dataset chaining.
• Decision Framework Support:
  • Default open-source Laya System-1 engine, with optional Jev API integration and deterministic rule fallbacks.

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Example Input (JSON)

{
  "yourName": "Jona",
  "yourCompany": "Eternal Labs",
  "yourValueProp": "We help B2B revenue teams identify high-intent accounts and automate personalized multi-channel outreach using AI.",
  "tone": "conversational",
  "outreachChannels": ["email", "linkedin", "cold_call_opener"],
  "minPriorityScore": 40,
  "maxProspects": 10,
  "decisionEngine": "laya",
  "prospects": [
    {
      "name": "Sarah Chen",
      "title": "VP of Engineering",
      "company": "Stripe",
      "website": "https://stripe.com",
      "industry": "Fintech",
      "intent_score": 85,
      "referral_tier": "strong",
      "signals": [
        "Hiring 15+ backend and AI engineers",
        "Recent infrastructure migration to Kubernetes"
      ]
    }
  ]
}

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Example Output (JSON)

{
  "prospect_name": "Sarah Chen",
  "prospect_title": "VP of Engineering",
  "company_name": "Stripe",
  "company_website": "https://stripe.com",
  "industry": "Fintech",
  "priority_score": 92,
  "personalization_score": 95,
  "recommended_channel": "email",
  "recommended_angle": "Hiring expansion & engineering scalability",
  "email_subject": "Scaling engineering at Stripe / mutual intro via Sarah",
  "email_body": "Hi Sarah,\n\nNoticed Stripe is actively expanding the backend engineering team across multiple hubs. Usually when engineering orgs scale this fast, onboarding velocity and infrastructure tooling become the primary bottleneck.\n\nAt Eternal Labs, we help engineering leaders streamline workflows with AI automation.\n\nWorth a brief 5-minute chat Tuesday morning to see how other fintech teams handle this?",
  "linkedin_connection_note": "Hi Sarah — noticed Stripe's impressive engineering expansion recently. Would love to connect and follow your work.",
  "linkedin_follow_up": "Thanks for connecting, Sarah! Saw you're scaling backend infrastructure. Would love to share how peer engineering VPs are automating tooling bottlenecks if helpful.",
  "cold_call_opener": "Hi Sarah, Jona with Eternal Labs. I saw your recent push hiring 15+ backend engineers — I know you're busy scaling the team, do you have 30 seconds for a quick question on engineering velocity?",
  "action_items": [
    "Send personalized email using hiring hook",
    "Send LinkedIn connection request referencing recent engineering growth",
    "Follow up within 3 business days if no response"
  ]
}

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How to Chain from Previous Actors

To automatically generate outreach for leads discovered in an earlier run:

1. Copy the Dataset ID from an earlier actor run (e.g. ai-prospect-intelligence or buying-intent-finder).
2. Paste it into the upstreamDatasetIdOrUrl field.
3. Outreach Intelligence will automatically fetch every prospect, evaluate their signals, and generate customized copy for all of them!

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Storage & Exports

• Dataset Tab: View structured JSON records, filter by priority score, or export to CSV / Excel.
• Key-Value Store: Download the OUTPUT_SUMMARY.json report summarizing total outreach briefs created, top angles, and channel distribution.