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Seo-Marketing.

React/LLM/Langchain/RAG/MLOps

Image Image

Marketing AI-Platform.

In this project, I leveraged Retrieval Augmented Generation (RAG) to enhance the capabilities of Generative AI for marketing, SEO, social media, and lead generation applications. By implementing RAG techniques, the Generative AI model was able to dynamically retrieve relevant information from external sources like databases, documents, and websites, allowing it to generate more accurate, up-to-date, and personalized content for marketing campaigns, SEO-optimized blog posts, social media chatbots and posts, as well as personalized lead qualification and outreach. The integration of a vector database for fast, semantic retrieval of data, combined with the scalability and automation benefits of Generative AI, enabled me to create a powerful solution that boosted efficiency and effectiveness across marketing, SEO, social media, and lead generation efforts.

I leveraged Retrieval Augmented Generation (RAG) to enhance the capabilities of Generative AI for marketing, SEO, social media, and lead generation applications, implementing RAG techniques to enable the model to retrieve information from databases, documents, and websites, creating a vector database to store and index the external data for fast, semantic search and retrieval, using the RAG-enhanced Generative AI to create personalized marketing content like blog posts, social media updates, email copy, and ads tailored to specific audiences by retrieving relevant data, generating content grounded in factual information from reliable sources to improve SEO and keep content fresh and up-to-date, automating content creation at scale while ensuring accuracy and relevance to boost efficiency for marketing teams, as well as exploring the use of Generative AI for social media management by developing chatbots and virtual assistants to provide personalized engagement and responses, creating timely, relevant social media posts tailored to audience interests, using Generative AI to engage with and qualify potential leads by asking relevant questions, providing information, and routing qualified leads to sales teams, and generating personalized outreach emails, messages and content for lead nurturing based on lead data and interests retrieved by RAG.

Project Info: Confidential

Category:

LLM optimized for marketing.

Infrastructure:

AWS, on-premise & Kubernetes

ML Frameworks:

Megatron-DeepSpeed, DeepSpeed, torchtune, Megatron-LM, Mesh Tensorflow.

Patent:

Ready

Pending Issues:

Security, Multichannels.

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