Data & AIConference40min
AI vs. Karen: Building Real-Time Sentiment Analysis Pipelines at Scale
This talk shows how to build AI-powered streaming pipelines with Apache Kafka and Flink to detect and respond to frustrated customers in real time. It covers embedding AI models in data streams, comparing LLMs and SLMs, addressing latency and scaling challenges, and includes a live end-to-end demo.
Josef GoldsteinWix
We’ve all heard that “the customer is always right". But let’s be honest, some customers are just impossible to please.
What if we could detect them before they turn into ALL-CAPS review bombers, in real-time?
In this talk, we’ll walk through how to build AI-powered streaming pipelines using Apache Kafka and Apache Flink that can detect frustrated users and respond in real time at massive scale.
We’ll explore how to embed AI models directly into data streams for live inference, discuss the trade-offs between using Large Language Models (LLMs) and Small Language Models (SLMs), and tackle the real-world challenges of latency, scale, and cost optimization in streaming AI architectures.
Finally, we’ll demo a live end-to-end example, from data ingestion to AI scoring and visualization, that you can later run on your own setup.
Whether you’re experienced in streaming systems or just curious about applying AI to real-world problems, this session will leave you with the needed practical foundation, insights, inspiration, and hopefully a few laughs along the way.
What if we could detect them before they turn into ALL-CAPS review bombers, in real-time?
In this talk, we’ll walk through how to build AI-powered streaming pipelines using Apache Kafka and Apache Flink that can detect frustrated users and respond in real time at massive scale.
We’ll explore how to embed AI models directly into data streams for live inference, discuss the trade-offs between using Large Language Models (LLMs) and Small Language Models (SLMs), and tackle the real-world challenges of latency, scale, and cost optimization in streaming AI architectures.
Finally, we’ll demo a live end-to-end example, from data ingestion to AI scoring and visualization, that you can later run on your own setup.
Whether you’re experienced in streaming systems or just curious about applying AI to real-world problems, this session will leave you with the needed practical foundation, insights, inspiration, and hopefully a few laughs along the way.
Josef Goldstein
The data and culture guy. Currently leading the Big Data Platform R&D at Wix.
Josef has over 15 years of experience building data intensive SaaS applications and growing the awesome teams that make them.
He believes that the secret sauce for creating sustainable complex systems is good design practices, effective communication between people, and automating everything. In his day to day he works tirelessly on building the culture necessary to support these values and propagate them to others, one pep-talk at a time.
Josef has over 15 years of experience building data intensive SaaS applications and growing the awesome teams that make them.
He believes that the secret sauce for creating sustainable complex systems is good design practices, effective communication between people, and automating everything. In his day to day he works tirelessly on building the culture necessary to support these values and propagate them to others, one pep-talk at a time.
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