Lead Hunter AI: Autonomous Multichannel Lead-Gen & Scoring Agent

Autonomous AI agent system: 30+ real-time source monitoring, rubric-based qualification, RAG capability verification, and instant CRM dispatch.

Client

B2B Professional Services & Consulting

Services

Autonomous Lead Generation Agents, Multichannel Monitoring, LLM Rubric Scoring, CRM Integration

Service

AI & Business Automation

15 min → 2 seconds

Turnaround Time

30+ real-time channels

Monitored Channels

Shadow Mode & 1-Click Approval

Verification Mode

Task

In high-ticket B2B consulting, turnaround speed on incoming requirements dictates conversion. Sales teams manually scanned dozens of industry chat groups and forums, missing up to 70% of high-intent inquiries while struggling to immediately cross-reference capabilities and pricing. The objective was to build an autonomous agent suite continuously parsing 30+ external channels, evaluating buyer intent, filtering spam, and drafting contextual proposals directly into the CRM.

Solution

Engineered in TypeScript and Python. Background collectors ingest messages across 30+ channels with rate-limit compliance. An LLM scoring rubric assesses intent from 0 to 100 while safety guardrails filter irrelevant noise. The agent consults an internal RAG knowledge base to align the prospect’s needs with verified case studies and rates. In Shadow Mode, the system pre-populates CRM deal cards with customized reply drafts for one-click human approval.

Autonomous Lead Engine Dataflow

┌─────────────────────────┐          Multichannel Ingestion       ┌──────────────────────────┐
│   30+ Public Channels   │ ────────────────────────────────────► │  Stream Collector Engine │
└─────────────────────────┘                                       └────────────┬─────────────┘
                                                                               │ Inbound Signals
                                                                               ▼
┌─────────────────────────┐          Rubric Grounding             ┌──────────────────────────┐
│   RAG Verification Base │ ◄──────────────────────────────────── │   LLM Scoring Engine     │
│   (Portfolios & Rates)  │ ────────────────────────────────────► │   (0-100 Score + Safety) │
└─────────────────────────┘          Contextual Proofs            └────────────┬─────────────┘
                                                                               │
                                                                               ▼
┌─────────────────────────┐          1-Click Dispatch             ┌──────────────────────────┐
│    CRM Pipeline Webhook │ ◄──────────────────────────────────── │   Shadow Mode Generator  │
│    (Enriched Deal Card) │                                       │   (Pre-composed Draft)   │
└─────────────────────────┘                                       └──────────────────────────┘

Lead Conversion Performance

Funnel Stage	Manual Sales Routine	Lead Hunter AI System
Response Turnaround	15–40 minutes (cold leads)	Under 2 seconds (instant capture)
Noise & Spam Elimination	100% manual review	85% discarded automatically
Proposal Personalization	Generic questionnaires	Contextual proposal citing past proofs

Key Features

Multichannel Stream (30+ Channels): Real-time aggregation across public forums, professional communities, and chats.
LLM Rubric Scoring & Safety Guard: Algorithmic buyer qualification scoring (0–100) discarding 85% of irrelevant chatter.
RAG Grounding: Instant cross-referencing with company portfolio proofs and accurate pricing tiers.
Shadow Mode Validation: Pre-generated contextual reply drafts enabling one-click human review and dispatch.
Automated CRM Pipelines: Enriched lead creation with structured summaries via secure webhooks.

Technologies

Architecture and Deployment

The autonomous lead engine reduced median response time from 15 minutes down to 2 seconds, producing a 3.2x increase in initial contact conversion and saving dozens of weekly manual sales hours.