Building Hyper-Personalized LLM Applications with Rich Contextual Data - DE4AI
Explore the concept of Full RAG (Retrieval-Augmented Generation) and its potential to revolutionize user experiences across industries in this 28-minute talk by Mike Del Balso, co-founder of Tecton. Examine four levels of context personalization, from ba…
Building Real-Time ML Features with a Feature Platform
Explore challenges in deploying ML pipelines and learn how feature stores and platforms solve data problems for production ML, enabling real-time processing and scaling.
Learn How to Clean Up Your Cloud-Native "DevOps Dumping Ground"
Learn to manage cloud-native automation with event-driven workflows, replacing inconsistent "digital duct tape" with reusable solutions for efficient DevOps practices and improved infrastructure control.
Native Kubernetes CI/CD Platform with Knative Pipeline
Explore Knative Pipeline for configuring and running CI/CD pipelines in Kubernetes, covering key features, use cases, and practical demonstrations for efficient application development.
Building a Python-Centric Feature Platform to Power Production AI Applications
Explore Tecton's journey in developing a Python-based platform for powering large-scale real-time AI applications. Learn about reliable solutions for productionizing AI using only Python skills.
Building a Unified Feature Platform with DuckDB and Arrow
Explore ML feature platform development using DuckDB and Arrow. Learn scaling strategies, DuckDB extension implementation, DeltaLake interoperability, and performance comparison with Spark.
Getting ML Applications Into Production - Expert Roundtable
Explore expert insights on overcoming challenges in ML application production, from organizational structure to tech stack bottlenecks, with practical strategies for efficient deployment.
Full RAG: A Modern Architecture for Hyperpersonalization
Explore Full RAG architecture for AI-driven hyperpersonalization, integrating real-time data and contextual insights to enhance recommendation systems beyond traditional models' capabilities.
Building a Fraud Detection Model with Feature Stores - Includes Shopify Case Study
Develop a real-time fraud detection system using ML data pipeline tools. Learn to build, deploy, and serve data pipelines with Feast and Tecton. Explore architectural patterns and model stages.
AI Innovations: The Power of Feature Platforms - MLOps Mini Summit
Explore feature platforms for production AI, including Tecton's unified approach, Cleo's custom solution, and DIY strategies for building scalable, flexible ML infrastructures.