Lyft Engineers Solve Multimodal Data Processing Problem with New Startup Eventual, Backed by $20M Series A Funding

Eventual, a data processing startup founded by Sammy Sidhu and Jay Chia, emerged from the challenges faced at Lyft’s autonomous vehicle program. While working there, the duo noticed a significant issue: the lack of a comprehensive tool to manage and process the vast amounts of unstructured data generated by self-driving cars, ranging from 3D scans and photos to text and audio. This gap meant that engineers spent a disproportionate amount of time—around 80%—on infrastructure, rather than focusing on core applications. Recognizing the need, Sidhu and Chia developed an internal multimodal data processing tool for Lyft. When Sidhu explored other job opportunities, potential employers often inquired about the possibility of implementing similar solutions, which inspired them to start Eventual. Their goal is to create a Python-native open-source data processing engine called Daft, designed to handle various data types efficiently. Founded in early 2022, Eventual launched the initial open-source version of Daft later that year. The release coincided with the surging interest in multimodal AI following the explosion of ChatGPT and similar generative models. These technologies required robust data processing capabilities across multiple formats, making Daft highly relevant and increasing its user base significantly. Eventual’s customer roster includes notable companies like Amazon, CloudKitchens, and Together AI. To further their mission, Eventual has raised significant venture capital. In March 2022, they secured a $7.5 million seed round led by CRV. Just eight months later, in December, the company raised a $20 million Series A round, led by Felicis Ventures, with additional investments from Microsoft’s M12 and Citi. The funds will be used to enhance Daft’s open-source features and develop a commercial product, slated for release in the third quarter of 2023. Astasia Myers, a general partner at Felicis Ventures, highlighted Eventual’s unique position in the market. She praised the company for being a first mover in addressing the growing need for multimodal data processing, especially given the rapid expansion of unstructured data. According to MarketsandMarkets, the multimodal AI industry is expected to grow at a 35% compound annual growth rate between 2023 and 2028. Myers also noted that the vast majority of data generated today is unstructured, emphasizing the relevance and potential impact of Daft. Daft aims to transform unstructured data infrastructure in the same way SQL revolutionized the handling of tabular data. This alignment with macro trends in data generation and AI development positions Eventual to address a crucial pain point across various sectors, including robotics, retail tech, and healthcare. As the company continues to refine and expand its offerings, it is poised to play a significant role in shaping the future of multimodal AI applications.