Platform Guide

The Leedrush architecture allows you to ingest, filter, and score revenue opportunities at scale.

To Whom This Product is Created

We don’t need millions of users. We need 50 serious sales teams.

Leedrush is engineered for high-intensity sales organizations that value precision over volume. Our ideal partners are teams that understand that 10 perfectly qualified, real-time opportunities are worth more than 10,000 stale leads.

The Philosophy

Traditional data brokers sell "lists". We sell "qualified state". Our platform ensures that every record entering your CRM is valid, active, and within your Ideal Customer Profile (ICP).

Data Architecture

Our pipeline processes data through six distinct stages to ensure maximum yield.

  • 01 Ingest Raw data ingestion from CSV, API, or Partner Streams.
  • 02 Normalize Standardization of Company Names, Job Titles, and Locations.
  • 03 Validate Real-time SMTP ping, DNS check, and disposable domain filtering.
  • 04 Enrich Appending 50+ data points including revenue, tech stack, and intent.
  • 05 Dedup Entity resolution to prevent duplicate records in your CRM.
  • 06 Score Final ICP scoring to prioritize high-value opportunities.

Dashboard & Batch Management

The central hub for all your data operations.

Recent Batches

The dashboard renders the 5 most recent batches for quick status checks. For a complete history of all your jobs, navigate to the Archive or My Batches page.

Batch Statuses

  • PROCESSING The pipeline is currently ingesting, validating, or enriching data.
  • COMPLETED The batch is ready for download or sync. Yield rates are final.
  • FAILED An error occurred. Check the logs or contact support.

Data Assets

Manage your raw files and suppression lists directly from the platform.

Uploaded Lists

All files (CSV, JSON) uploaded via the dashboard are stored here securely. You can reference them for future re-runs or audits.

Suppression Lists

Ensure compliance by uploading domains or emails that should never be contacted. These records are automatically stripped from all future batches.

Normalization Engine

Garbage in, garbage out. We clean data before it ever hits the enrichment layer.

Company Names

We strip legal entities (Inc, LLC, Ltd) and normalize variations.

  • Alphabet Inc. → Alphabet
  • IBM Corp → IBM

Job Titles

We map thousands of creative job titles to standard seniority levels and departments.

  • VP of People Ops → VP - HR
  • Head of Engineering → Head - Engineering

Multi-Signal Validation

We don't trust vendor flags. We verify contactability in real-time.

Email Validation

SMTP Handshake & Zerobounce catch-all detection.

Phone Verification

Line activity & Carrier lookup.

Compliance

GDPR & CCPA suppression lists.

Predictive Scoring

Our model evaluates leads based on 5 core dimensions to assign a 0-100 fit score.

  • Firmographics (30%): Industry, Employee Count, Revenue (Enriched via Clearbit & Apollo).
  • Persona (25%): Seniority, Department, Tenure.
  • Technographics (15%): Current stack (e.g., Uses Salesforce, AWS).
  • Intent (15%): Recent hiring or funding signals.
  • Completeness (15%): Presence of direct dial, LinkedIn, etc.

Data Output & Integration

How you receive your opportunities.

Standard JSON Output

{
  "lead_id": "opp_88723",
  "score": 92,
  "status": "QUALIFIED",
  "contact": {
    "full_name": "Sarah Connor",
    "title_normalized": "VP of Operations",
    "email": "sarah@skynet.com",
    "phones": ["+1-555-0199"]
  },
  "company": {
    "name": "Skynet Cyberdyne",
    "domain": "skynet.com",
    "technologies": ["AWS", "Python", "React"]
  }
}

Real-time ICP Validation

Real-time ICP validation is the process of evaluating incoming leads at the moment they enter the system, before any contact is initiated by the sales team.

What Is ICP?

ICP (Ideal Customer Profile) is a description of the ideal customer a business should focus on, based on:

  • Conversion potential
  • Average deal size
  • Deal velocity
  • Real need for the product

Instead of calling or messaging first and only later realizing that a lead is not a good fit, the system performs this evaluation in advance and automatically.

How It Works in Practice

Leedrush:

  • Accepts an incoming contact or a lead database
  • Validates each lead against the defined ICP in real time
  • Analyzes key parameters such as company size, region, role, industry, and purchasing power
  • Filters out unsuitable contacts before an SDR spends time on them
Result
SDRs work only with leads that have real deal potential, rather than wasting time on noise.

CRM Auto-push

CRM auto-push is the automatic delivery of validated leads directly into a CRM system without user involvement.

Traditional vs. Leedrush Workflow

Traditional
  • CSV exports
  • Manual imports
  • Copying and pasting data
  • Errors and context loss
Leedrush Auto-push
  • Automatically
  • Immediately after validation
  • No checks required
  • Direct to HubSpot/Pipedrive
fast-track
The SDR opens the CRM and sees clean, pre-filtered contacts that are ready for immediate action.

Who This Solution Is For (Leedrush ICP)

Leedrush is designed for:

  • outbound SDRs,
  • small and mid-sized sales teams,
  • lean teams with high workload per individual.

This is not an enterprise solution with dozens of integrations and complex processes.

It is built for:

  • SMBs,
  • automated outbound workflows,
  • teams that prioritize:
    • precision,
    • speed,
    • reasonable pricing.

Why Leedrush Wins

Precision

  • The focus is not on lead volume,
  • but on lead quality,
  • validation happens in real time,
  • fewer irrelevant contacts and higher conversion rates.

Affordability

  • no enterprise-level pricing,
  • suitable for daily use,
  • budget efficiency due to the absence of paid "noise".
Bottom line:
SDRs pay not for processing junk data, but for real opportunities to sell.

Supported Integrations

Salesforce
HubSpot
Pipedrive

🚀 Smart Caching

Intelligent multi-level caching system that dramatically reduces processing time and costs.

Benefits

  • ⚡ 94% cache hit rate - Most requests served instantly
  • 🚀 90% latency reduction - Near-instant results
  • 💰 Lower costs - Fewer API calls needed
  • 🎯 Similarity matching - Finds similar leads automatically

How It Works

L1 Cache (In-Memory LRU)

Ultra-fast lookup (<1ms), 1000 entry capacity, 100ms TTL

L2 Cache (Redis)

Persistent, distributed cache with unlimited capacity and adaptive TTL (1-30 days)

Similarity Matching

85% similarity threshold, matches variations (e.g., 'Jon Smith' → 'John Smith'), fuzzy matching on name, company, domain

Intelligent TTL Manager

Confidence-based adaptation: Low confidence (<70%): 0.5x TTL, High confidence (>95%): 1.5x TTL

What This Means for You

  • Duplicate Leads: Processed instantly (0s latency)
  • Similar Variations: Automatically matched
  • Cost Savings: 94% of requests served from cache

🤖 Predictive Enrichment

AI-powered system that predicts which leads you'll need next and pre-enriches them in the background.

Benefits

  • ⚡ 0s perceived latency for 80% of requests
  • 🤖 Pattern detection - Identifies batch patterns automatically
  • 📈 +100% throughput - Parallel background processing
  • 💰 Cost efficient - Background enrichment during idle time

How It Works

Pattern Analysis

Detects company batches, identifies sequential patterns, analyzes domain patterns

Prediction Engine

Forecasts likely next requests, generates prediction candidates, prioritizes by probability

Background Enrichment

Pre-processes predictions invisibly, resource-aware throttling, no user-facing delays

Instant Delivery

Cached results served immediately, 0s latency for predicted requests, seamless user experience

Real-World Example

Upload 100 employees from 'TechCorp' → System detects batch pattern → Pre-enriches predicted candidates → 80% already enriched when you upload them!

Pattern Types Detected

  • Company Batches: Multiple leads from same company
  • Sequential Patterns: Alphabetical employee lists
  • Domain Patterns: Common email domain

✅ Multi-Source Validation

Cross-validate data from multiple providers to ensure maximum accuracy and coverage.

Benefits

  • ✅ 99%+ data coverage - Multiple fallback sources
  • ✅ 99%+ data quality - Cross-validation ensures accuracy
  • 🎯 +20% confidence vs single-source enrichment
  • 🔍 Transparent attribution - See which sources agree

How It Works

Parallel Queries

Query Hunter.io, Clearbit, Snov.io simultaneously (150ms average), graceful degradation if provider fails

Consensus Algorithm

Weighted voting resolves conflicts. Provider reliability weights: Hunter.io (40%), Clearbit (30%), Snov.io (20%)

Quality Validation

Automated quality checks, email format validation, domain consistency checks, confidence scoring

Best Result

Returns highest-confidence merged data with source attribution and agreement scores

Data Fields Validated

  • Contact Information: Email, phone, job title, LinkedIn URL
  • Company Information: Name, industry, company size, revenue
  • Enrichment Metadata: Data sources used, agreement scores, confidence levels

What This Means for You

  • Higher Accuracy: 99%+ data quality vs 90% single-source
  • Better Coverage: 99%+ coverage vs 95% single-source
  • Transparency: See which sources agree and understand confidence levels