What is Pipl.ai?
Pipl.ai is a comprehensive cold email platform that leverages artificial intelligence to revolutionize outreach campaigns. The platform combines advanced email warming technology, AI-driven personalization, and sophisticated automation features to help businesses achieve up to 99.8% inbox placement rates and 45% higher reply rates.
The platform stands out with its unlimited email accounts capability, built-in enrichment tools that gather data from 35+ sources, and AI-powered campaign generation that creates personalized sequences in minutes. Its custom AI models ensure human-like interactions and behavior patterns, while the advanced deliverability controls help maintain high inbox placement rates.
Features
- Email Warm-up: Private warm-up pool with 45k+ accounts and custom AI model for human-like interactions
- AI Campaign Generation: Creates complete email sequences in minutes using AI trained on 1400+ campaigns
- Mass Personalization: Built-in enrichment from 35+ sources with AI personalization engine
- Deliverability Controls: Advanced settings achieving 99.8% inbox hit rate
- Unlimited Scaling: Connect unlimited inboxes and import unlimited prospects
- Built-in Tools: Email validation, finder, and data enrichment capabilities
Use Cases
- Cold email outreach campaigns
- Sales prospecting automation
- Email deliverability improvement
- Lead generation
- Sales team automation
- Marketing campaign personalization
- Business development outreach
FAQs
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How does the email warming feature work?
The email warming feature uses a combination of real and artificial words to bypass filtering algorithms, ensuring emails reach their intended recipients. Users can customize tracking words and schedule to fit their business needs. -
Can I customize the warm-up settings?
Yes, users can tailor warm-up settings to mirror typical business language, select specific warm-up schedules, and warm-up custom tracking domains for improved deliverability.
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Pipl.ai Uptime Monitor
Average Uptime
100%
Average Response Time
227.8 ms
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