Custom RAG Solutions with LLMs for Data-Driven Insights by Enrique Sampaio dos SantosCustom RAG Solutions with LLMs for Data-Driven Insights by Enrique Sampaio dos Santos

Custom RAG Solutions with LLMs for Data-Driven Insights

Enrique Sampaio dos Santos

Starting at

/hr

About this service

Summary

Bespoke RAG Solutions with Large Language Models

I specialize in developing tailored Retrieval-Augmented Generation (RAG) solutions using large language models (LLMs) to unlock actionable insights from your data. My service encompasses every stage of the process, ensuring a seamless and effective implementation:

Data Handling: Starting with data extraction and cleaning, I prepare your datasets for use in the RAG system. This includes enrichment with auxiliary information and creating robust embeddings to enable high-accuracy retrieval.

Custom Chain Development: I design and implement the RAG chain, ensuring it integrates seamlessly with your LLM of choice to handle user queries with precision and relevance.

Prompt Optimization: Using prompt engineering techniques, I fine-tune the interaction between your data and the LLM, achieving optimal performance tailored to your specific use cases.

Scalable Deployment: The solution is deployed as a secure and scalable API endpoint, ready to integrate with your systems. Additionally, I can develop custom applications, such as chatbots, to provide user-friendly interfaces for end-users.

This service is ideal for organizations seeking to harness their data efficiently, whether for operational decision-making, customer support, or enhancing internal knowledge accessibility. With my end-to-end approach, I deliver solutions that are not only technically sound but also aligned with your strategic goals.

What's included

Data Preparation and Preprocessing
- Extraction of data from client-provided or public sources. - Data cleaning and normalization to ensure consistency. - Enrichment and metadata aggregation for contextual relevance.
Vectorization and Storage
- Implementation of embedding models for data vectorization. - Setup of a vector database for efficient retrieval and indexing.
Chain Development
- Design and development of the retrieval-augmented generation (RAG) chain. - Integration with the chosen LLM to handle queries and generate responses.
Prompt Engineering
- Crafting and testing of prompts to optimize model responses. - Iterative refinement for specific use cases, including edge scenarios.
Model Deployment
- Deployment of the RAG solution as a scalable and secure API endpoint. - Integration with the client’s existing infrastructure or tools.
Custom Application Integration (Optional)
- Building a custom chatbot or interface for specific platforms, such as Microsoft Teams, Slack, or a web application.
Testing and Validation
- Functional and performance testing of the RAG solution. - Validation of the response quality against predefined benchmarks.
Documentation and Support
- Technical documentation for the chain, APIs, and overall architecture. - User guide for interacting with the solution. - Initial support and handover training for the client’s team.

Skills and tools

Prompt Engineer

Backend Engineer

AI Chatbot Developer

ChatGPT

LangChain

Python

More services

Expert Backend and Frontend Development for Your Website

STARTING AT

$30/hour

hourly rate