Automated Sales Outreach Tool

We wanted to make a sales outreach tool that could write personalized emails at scale. Here’s how we designed and learned along the way.

System Architecture

The system works in these main components:

1. Input Processing
   • CSV file upload or LinkedIn URL input
   • Data cleaning and validation
2. Data Enrichment
   • Proxycurl API integration for profile data
   • Company information extraction
   • Data standardization
3. RAG Pipeline
   • Document processing and chunking
   • FAISS vector indexing
   • Context retrieval system
4. Email Generation
   • Context preparation
   • LLM integration
   • Output formatting

Technical Implementation

RAG System

• Vector store built on FAISS for efficient similarity search
• Document chunking with overlap for context preservation
• Embedding generation using Ada-002
• Context retrieval based on cosine similarity

Personalization Engine

• LLM for email generation
• Custom prompt engineering for sales context
• Hybrid retrieval combining exact and semantic search
• Real-time content adaptation

Performance Metrics

• Average response time: 3-5 seconds
• Context retrieval accuracy: 89%
• Daily email generation capacity: 1000+
• Storage efficiency: ~100MB per 10,000 documents

Key Technical Features

1. Scalable Architecture

   • Async processing for batch operations
   • Distributed vector storage
   • Queue-based job processing

2. Data Security

   • End-to-end encryption
   • Rate limiting
   • Access control implementation

3. Integration Capabilities

   • REST API endpoints
   • Webhook support
   • CSV/JSON export options

Results

• 3x faster email composition
• 70% reduction in manual review time
• 45% improvement in response rates
• Processing capacity: 10,000+ emails/day

Future Development

We’re working on:

• Multi-language support
• A/B testing framework
• Advanced analytics dashboard
• Custom model fine-tuning

For more information or technical discussions, contact our engineering team at engineering@adanomad.com