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Outread

A B2B outreach platform that combines AI-powered prospect discovery with multi-channel engagement automation.

Want to see the code or get access? Let me know!

PRODUCT WALKTHROUGH

Key Features in Action

Natural Language Search

Describe your ideal customer in plain English and get instant results. The system uses Elasticsearch with custom analyzers to deliver sub-50ms search latency across thousands of companies.

Outread Search Interface
Contact Discovery

Automated Contact Discovery

AI identifies the best decision-makers at target companies. The system analyzes company structure, role hierarchy, and contact information to find the right person for your outreach.

AI-Powered Personalization

Generate personalized messages at scale. The AI analyzes company context, prospect role, and your product offering to craft compelling, human-like outreach messages.

Custom Message Generation
Analytics Dashboard

Real-Time Analytics

Track campaign performance with detailed analytics. Monitor open rates, response rates, and conversion metrics across all your outreach channels in one unified dashboard.

1000+
Companies Processed
42.8%
Average Response Rate
10x
Outreach Scale
50ms
Search Latency

OVERVIEW

I built Outread to solve a problem I saw repeatedly: sales teams wasting 40% of their time on manual prospecting. The platform automates the entire workflow - from finding companies that match your ideal customer profile to identifying the right decision-makers and sending personalized messages across multiple channels.

The core innovation is the natural language search. Users describe their ideal customer in plain English, and the system returns matching companies from the database with sub-50ms latency. From there, AI identifies the best contacts to reach and generates personalized outreach messages.

TECHNOLOGY

Frontend
Next.jsReactTypeScriptTailwind
Backend
Node.jsPythonFastAPI
Database
PostgreSQLRedisElasticsearch
AI
OpenAI GPT-4LangChainCustom NLP
Infrastructure
AWSDockerKubernetes

CHALLENGES

Sub-50ms search across large datasets

Implemented Elasticsearch with custom analyzers and multi-tier caching. Query times dropped from 2s to 50ms average.

Rate limiting across multiple APIs

Built a unified rate limiter with token bucket algorithm and priority queuing for LinkedIn, email, and WhatsApp APIs.

AI message quality at scale

Developed prompt engineering pipeline with A/B testing and quality scoring to maintain personalization quality across thousands of messages.

MY ROLE

I architected and built the entire platform as the sole developer. This included system design, database schema, AI integration, frontend development, API integrations (LinkedIn, email providers, WhatsApp), and cloud infrastructure setup on AWS.

Interested in working together?

I'm always open to discussing new projects.

Get in Touch →