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Streaming & Ingestion

Data pipelines for AI assistants
The backbone of successful AI systems
 • Paul Iusztin
Build a semantic news search engine with 0 delay
How to build a real-time news search engine using Kafka, vector DBs, RAG and streaming engines.
 • Paul Iusztin
Scalable RAG ingestion pipeline using 74.3% less code
End-to-end implementation for an advanced RAG feature pipeline
 • Paul Iusztin
SOTA Python Streaming Pipelines for Fine-tuning LLMs and RAG - in Real-Time!
Use a Python streaming engine to populate a feature store from 4+ data sources
 • Paul Iusztin
How to build a real-time News Search Engine using Vector DBs
A hands-on guide to implementing a live news aggregating streaming pipeline with Apache Kafka, Bytewax, and Upstash Vector Database.
 • Alex Razvant
CDC: Enabling Event-Driven Architectures
Transforming Data Streams: The Core of Event-Driven Architectures
 • Vesa Alexandru
The Importance of Data Pipelines in the Era of Generative AI
From unstructured data crawling to structured valuable data
 • Vesa Alexandru
A Real-time Retrieval System for RAG on Social Media Data
Use a streaming engine to populate a vector DB in real time. Use rerank & UMAP to improve the accuracy of your retrieved documents.
 • Paul Iusztin
DML: How to implement a streaming pipeline to populate a vector DB for real-time RAG?
Lesson 4 | The Hands-on LLMs Series
 • Paul Iusztin
DML: Why & what do you need a streaming pipeline when implementing RAG in your LLM applications?
Lesson 3 | The Hands-on LLMs Series
 • Paul Iusztin
DML: Synced Vector DBs - A Guide to Streaming Pipelines for Real-Time RAG in Your LLM Applications
Hello there, I am Paul Iusztin 👋🏼
 • Paul Iusztin
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