Cold Email Generator Using LLM

[SimranShaikh20]

Problem Statement
In the competitive world of software services, companies like TCS, Infosys, and Attic Technologies compete to acquire new clients by providing high-quality software solutions. Their clients—large corporations such as Nike, JP Morgan, and Kroger—often post job openings indicating specific technology needs. These job posts provide insight into client requirements for software engineering, especially in AI/ML and DevOps, which these service providers can leverage to offer contract-based solutions.

Solution Overview
The Cold Email Generator tool will take a job posting as input, extract required skills, and automatically craft a customized cold email that highlights the service provider’s expertise in the relevant domains. The generated email will focus on how the service provider's team can meet the client’s requirements on a contract basis, showcasing previous project experience and relevant skills to make the outreach compelling.

Approach to be followed are here -
Data Extraction
Skill Matching and Email Generation
Components and Technology- LLM (Lama 3.1), Chroma ADB (Vector Store) , LangChain

Objective: Sales teams at these software service companies frequently use cold emailing as a technique to approach potential clients. However, crafting personalized, skill-relevant cold emails can be time-consuming. This project aims to automate the process of generating highly relevant cold emails by analyzing job postings and matching them with the service provider's expertise. The goal is to save time and improve the effectiveness of these outreach efforts by using an LLM (Large Language Model) to generate context-specific cold emails.

@UTSAVS26 liked my project idea assign me task i will on it !

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[UTSAVS26]

@SimranShaikh20 please read this #1073

[github-actions]

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