Agent in a Box

Autonomous B2B Lead Generation & Multi-Channel Qualification Agent

sales

AI Agent for Lead Generation: Autonomous B2B Multi-Channel Qualification

Problem Statement

B2B Sales Development Representatives (SDRs) currently spend 60-70% of their time on "grunt work": searching for prospects, verifying contact data, and manually qualifying leads through repetitive initial outreach. For startups, this creates a massive bottleneck where high-value account executives are stuck performing low-level data entry instead of closing deals.

The core issue is the "Leads-to-Pipeline" gap. Thousands of raw signals (LinkedIn profile views, job changes, funding rounds) go ignored because teams lack the bandwidth to process them. When leads do enter the CRM, they are often stale or unqualified, leading to a 2% conversion rate from cold outreach. Manual qualification is also inconsistent; one SDR might follow up three times, while another gives up after one. This inconsistency results in a high Customer Acquisition Cost (CAC) and a "leaky bucket" sales funnel. Startups need an automated sales prospecting system that can autonomously identify high-intent prospects, enrich their profiles with real-time business context, and perform the initial tier-1 qualification via asynchronous channels before a human ever touches the record.

What the Agent Does/Doesn't Do

What it does:

  • Monitors intent triggers (funding, hiring, tech stack changes) via Apollo and LinkedIn.
  • Enriches leads with deep-level research (latest 10-K filings, recent news, podcast appearances) using a hyper-personalized cold outreach researcher methodology.
  • Scores leads based on a custom ICP (Ideal Customer Profile) matrix for lead scoring automation.
  • Conducts initial outreach and handles "not interested" or "wrong person" objections.
  • Books discovery calls directly onto AE calendars when qualification criteria are met.

What it doesn't do:

  • Negotiate pricing or close contracts.
  • Handle complex multi-stakeholder enterprise demos.
  • Manage long-term relationship building (Post-Discovery).
  • Cold call via phone (limited to text-based multi-channel).

Workflow

  1. Trigger & Extraction: Agent monitors LinkedIn Sales Navigator and Apollo for specific triggers (e.g., "New VP of Engineering hired").
    • Input: ICP Parameters (Title, Industry, Revenue).
    • Output: Raw Lead List (Names, Companies).
  2. Contextual Research: Agent scrapes the company’s "News" page and the prospect’s recent LinkedIn activity using Perplexity API.
    • Input: Lead Company URL.
    • Output: 3-bullet summary of "Current Pain Points."
  3. ICP Scoring: Agent compares research against the "Golden Lead" profile using a LLM-based scoring logic, similar to a lead qualification agent.
    • Input: Research Summary + ICP Matrix.
    • Output: Lead Score (1-100) and "Reason for Score."
  4. Multi-Channel Outreach: Agent drafts and sends a hyper-personalized sequence via email (Instantly.ai) and LinkedIn (HeyReach).
    • Input: Lead Score + Contextual Research.
    • Output: Sent Messages.
  5. Qualification & Handoff: Agent monitors replies. If a reply is positive, it asks 2-3 qualifying questions. If criteria are met, it sends a Calendly link and ensures CRM AI integration with HubSpot or Salesforce.
    • Input: Prospect Reply.
    • Output: Booked Meeting in CRM.

Tool Stack

  • Apollo.io - Lead database and intent signals.
    • Pricing: Basic: $49/user/mo (annual); Professional: $79-$99/user/mo (annual) (Pricing) ✓ Verified 2026-01-13
    • Documentation
  • Make.com - Workflow orchestration.
  • OpenAI GPT-4o - Intelligence for scoring and drafting.
  • Perplexity API - Real-time web search for deep research.
    • Pricing: $5 API credit included in Pro plans ($20/month); usage-based thereafter (Pricing) ✓ Verified 2026-01-13
    • Documentation
  • Instantly.ai - Cold email automation with deliverability tools.
    • Pricing: [Unverified] (Typically starts at $37/mo)
    • Documentation
  • HeyReach - Automated LinkedIn outreach.
    • Pricing: [Unverified] (Typically starts at $79/mo)
  • Clay - Data enrichment and waterfalling.
    • Pricing: [Unverified] (Typically starts at $149/mo)
  • HubSpot - CRM for lead management and handoff.
  • Salesforce - Enterprise CRM integration.
  • LinkedIn Sales Navigator - Prospecting and intent signals.
    • Pricing: [Unverified]
  • Calendly - Meeting scheduling.
    • Pricing: [Unverified]

Quick Integration

HubSpot: Fetching Recent Deals

import requests

# HubSpot API endpoint for retrieving the CRM deals pipeline
url = "https://api.hubapi.com/crm/v3/objects/deals"

headers = {
    'accept': "application/json",
    'authorization': "Bearer YOUR_ACCESS_TOKEN"
}

params = {
    "limit": "10",
    "properties": "dealname,amount,closedate,pipeline,dealstage",
    "archived": "false"
}

try:
    response = requests.get(url, headers=headers, params=params)
    response.raise_for_status()
    data = response.json()
    
    print("Recent Deals for Cash Flow Forecasting:")
    for deal in data.get('results', []):
        props = deal.get('properties', {})\n        print(f"Deal: {props.get('dealname')} | Amount: ${props.get('amount')} | Close Date: {props.get('closedate')}")

except requests.exceptions.RequestException as e:
    print(f"Error fetching HubSpot data: {e}")

Source: HubSpot Docs

Salesforce: Creating a Triage Case

import requests

# Configuration
INSTANCE_URL = 'https://your-instance.salesforce.com'
ACCESS_TOKEN = 'YOUR_ACCESS_TOKEN'
API_VERSION = 'v60.0'

url = f"{INSTANCE_URL}/services/data/{API_VERSION}/sobjects/Case/"

payload = {
    "Subject": "Urgent: Team-wide lockout reported",
    "Description": "Customer sentiment: Frustrated. Impact: Entire team unable to access platform.",
    "Priority": "High",
    "Origin": "Web",
    "Status": "New"
}

headers = {
    "Authorization": f"Bearer {ACCESS_TOKEN}",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

if response.status_code == 201:
    print(f"Success! Case Created. ID: {response.json().get('id')}")
else:
    print(f"Failed to create case: {response.status_code}")

Source: Salesforce Docs

Prompt Skeletons

(Existing prompt skeletons would be placed here)