Welcome to the Eventual blog
Join us as we explore innovative ways to handle multimodal datasets, optimize performance, and simplify your data workflows.
After the First Run
Using Daft's observability tools to uncover performance pitfalls
Making GPUs Zoom (Part 1)
How Daft is approaching large-scale model inference with advanced GPU optimizations for faster multimodal AI workloads
End-to-End Distributed PDF Processing Pipeline
Build production-ready PDF processing pipelines with distributed computing, OCR, spatial analysis, and GPU embeddings
How to Build Scalable, End-to-end Batch Inference Pipelines with Daft
Daft makes it easy to express these pipelines end-to-end, while seamlessly scaling them up to handle massive workloads.
Embedding Millions of Text Documents With Qwen3
Learn how to achieve near-100% GPU utilization processing millions of text documents with Qwen3 embeddings.
Processing 300K Images Without OOM
A Streaming Solution
We cloned over 15,000 repos to find the best developers
An adventure in AI and data engineering to analyze developers across Github
High-Performance File System Support With DeepSeek 3FS
Learn how Daft integrates with DeepSeek SmallPond 3FS to deliver faster file access and efficient data handling for modern workloads.
Introducing Daft-SQL for High-Performance Data Exploration
A SQL API enabling users to interact with their data in a new but familiar way. Learn how Daft-SQL brings fast, scalable querying to multimodal workloads, helping teams explore large datasets efficiently with a distributed engine.