Eventual, a startup founded by former Lyft engineers Sammy Sidhu and Jay Chia, has secured $30 million to expand Daft — an open-source, Python-native engine built for processing complex, multimodal data. The company aims to address a core bottleneck they witnessed while working on Lyft’s autonomous vehicle program: lack of reliable infrastructure for managing unstructured data across formats like 3D scans, text, images, and audio.
During their time at Lyft, engineers had to stitch together open-source tools to process disparate data types, creating a fragile pipeline with reliability issues. According to Sidhu, Eventual’s CEO, even PhDs across the AV industry spent 80% of their time fixing infrastructure instead of building applications.
Recognizing the industry-wide need, Sidhu and Chia built Daft to unify data processing for AI developers and companies working with high-dimensional, multimodal inputs. The idea for Eventual grew after Sidhu was repeatedly asked in interviews about applying his internal Lyft tooling to other companies' problems.
Daft is designed to process data quickly and efficiently across formats, with a goal of becoming the go-to engine for modern AI workloads. The new funding round positions Eventual to evolve Daft into a foundational layer for AI infrastructure.
To read more, visit the official announcement here.