AI Qualification Engine
AI-powered lead scoring, junk removal, and persona classification for B2B sales intelligence
The AI Qualification Engine is the quality gate of the AI lead generation pipeline. It normalizes multi-language names (Latin, CJK, Cyrillic, Arabic), removes junk contacts with 14 detection rules, scores every lead across 5 dimensions (title authority, email quality, completeness, LinkedIn enrichment presence, target match), classifies personas for AI outbound automation, and deduplicates across companies. Only qualified contacts pass through to the lead enrichment platform export.
Pipeline Stages
Each stage executes automatically, escalating only when needed.
Normalize
Language detection (Latin/CJK/Cyrillic/Arabic), name normalization, email format validation, phone standardization for the B2B sales intelligence pipeline.
Clean
14-rule junk removal for AI lead generation: missing names, invalid emails, role emails (info@, support@), navigation text, UI elements, social handles misidentified as names, generic contacts, noise strings.
Score
5-dimension scoring for AI outbound automation: Title Authority (C-suite=5, VP=4, Director=3) + Email Quality (verified=high, predicted=medium) + Completeness (how many fields filled) + LinkedIn enrichment (profile found) + Target Match (industry/role fit).
Output
Cross-company deduplication (email-based + name+company matching), priority classification (High/Medium/Low), persona labels, streaming dataset push to the sales intelligence API.
Normalize
Language detection (Latin/CJK/Cyrillic/Arabic), name normalization, email format validation, phone standardization for the B2B sales intelligence pipeline.
Clean
14-rule junk removal for AI lead generation: missing names, invalid emails, role emails (info@, support@), navigation text, UI elements, social handles misidentified as names, generic contacts, noise strings.
Score
5-dimension scoring for AI outbound automation: Title Authority (C-suite=5, VP=4, Director=3) + Email Quality (verified=high, predicted=medium) + Completeness (how many fields filled) + LinkedIn enrichment (profile found) + Target Match (industry/role fit).
Output
Cross-company deduplication (email-based + name+company matching), priority classification (High/Medium/Low), persona labels, streaming dataset push to the sales intelligence API.
Normalize
Language detection (Latin/CJK/Cyrillic/Arabic), name normalization, email format validation, phone standardization for the B2B sales intelligence pipeline.
Clean
14-rule junk removal for AI lead generation: missing names, invalid emails, role emails (info@, support@), navigation text, UI elements, social handles misidentified as names, generic contacts, noise strings.
Score
5-dimension scoring for AI outbound automation: Title Authority (C-suite=5, VP=4, Director=3) + Email Quality (verified=high, predicted=medium) + Completeness (how many fields filled) + LinkedIn enrichment (profile found) + Target Match (industry/role fit).
Output
Cross-company deduplication (email-based + name+company matching), priority classification (High/Medium/Low), persona labels, streaming dataset push to the sales intelligence API.
Key Capabilities
14-Rule Junk Detection for AI Lead Generation
Catches: missing first/last names, invalid email syntax, role-based emails (info@, admin@, support@), navigation text scraped as names, social handles, generic contacts, noise strings, duplicate patterns for clean B2B sales intelligence.
5-Dimension Lead Scoring
Title Authority (seniority level 1-5), Email Quality (verified/predicted/none), Completeness (% of fields populated), LinkedIn enrichment (profile found/not), Target Match (industry and role alignment). Weighted combination produces 0-100 score for AI outbound automation.
Multi-Language Support
Name normalization handles Latin, CJK (Chinese/Japanese/Korean), Cyrillic, and Arabic scripts. Language detection determines correct parsing rules automatically for global AI lead generation.
Persona Classification for Sales Intelligence
4 persona types: Economic Buyer (budget authority), Champion (internal advocate), Technical Evaluator (technical decision maker), Influencer (can recommend but not decide). Critical for AI outbound automation targeting.
Cross-Company Dedup
Email-based primary matching plus fuzzy name+company matching catches the same person listed at multiple companies or in multiple data sources within the lead enrichment platform.
Combined Intelligence Score
Aggregates domain intelligence, social presence, company trust, website quality, and individual lead score into a single B2B sales intelligence metric for prioritization.
Accepted Inputs
- Inline contact array from upstream actors
- CSV/Excel with contact columns
- Public URL to contact data
- Apify KV Store key
Configuration
- Max Results: limit output size
- Domain Intel context: inject domain intelligence data
- Social Data context: inject social profile data
- Company Data context: inject company metadata
- Website Data context: inject crawl results
See It In Action
Frequently Asked Questions
Everything you need to know about our platform.
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