You will get custom Contextual RAG for great GenAI using your own vast knowledge corpus


Project details
Retrieval Augmented Generation (RAG) is at the frontier of AI with tools like ChatGPT and Claude. Contextual RAG takes it a step further and is essential producing accurate and truthful results from generative AI when you need to customize responses to use your unique, enterprise-sized knowledge base.
This project creates a CRAG system including API connections, word embeddings, vector databases, and BM25. At the end, users will be able to chat with a vast swathe of your company's knowledge, going beyond vanilla LLM use for a highly-tailored, bespoke, and powerful productivity experience.
This project creates a CRAG system including API connections, word embeddings, vector databases, and BM25. At the end, users will be able to chat with a vast swathe of your company's knowledge, going beyond vanilla LLM use for a highly-tailored, bespoke, and powerful productivity experience.
AI Algorithms
Large Language Model, Multimodal Large Language ModelAI Applications
AI Chatbot, AI Content Creation, AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Models
ChatGPT, GPT-4, LLaMAWhat's included $1,990
These options are included with the project scope.
$1,990
- Delivery Time 17 days
- Number of Revisions 2
- AI Model Integration
- Database Integration
- Detailed Code Comments
- Model Deployment
- Model Documentation
- Model Testing & Optimization
- Model Tuning
- Natural Language Processing
- Prompt Engineering
- Source Code
Frequently asked questions
About Glen
AI/Machine Learning, LLM, and GenAI Product Expert who codes in Python
Austin, United States - 4:51 am local time
SmarterX: built successful, high-scale NLP applications/APIs on GPT (including model fine-tuning), with Elasticsearch, Datafiniti, and synthetic data generators and testing tools built in Python, plus techniques like XGBoost.
WriteStronger: integrated Llama 3.2 into privacy-first desktop application, using Python, Node.js, and Electron.
iMerit and Alegion: applied computer vision ML models (detection and localization) to applications in e‑commerce, fashion, and autonomous vehicles at video scale.
TALK TO ME if you need consultation on or development of up-to-date generative AI and ML techniques like embeddings, vector search, RAG, RLHF, DPO, and Contextual Retrieval with BM25.
Just need help with the basics? I can teach you how to get productive with ChatGPT and Anthropic Claude at modest rates.
Get in touch!
Steps for completing your project
After purchasing the project, send requirements so Glen can start the project.
Delivery time starts when Glen receives requirements from you.
Glen works on your project following the steps below.
Revisions may occur after the delivery date.
Optional checkup (free, AFTER delivery)
We touch base to see how your users are progressing with their new custom generative AI solution.