When Sammy Sidhu and Jay Chia were software engineers at Lyft’s self-driving car team, they kept running into the same frustrating problem — too much data, and not enough good ways to handle it.
The autonomous vehicles were generating all kinds of unstructured data: video, audio, 3D scans, text. But there wasn’t a single tool that could process it all together. The result? Brilliant engineers were wasting hours trying to glue together a bunch of mismatched tools, just to get anything working.
“We had all these top minds in robotics and AI,” said Sidhu, now co-founder and CEO of Eventual, “but they were spending most of their time just trying to make the infrastructure work.”
A New Idea Takes Shape
Sidhu and Chia eventually built an internal tool at Lyft to handle all that messy data more efficiently. But it wasn’t until Sidhu started interviewing for new jobs that he realized how valuable their solution really was.
Company after company asked him if he could build a similar tool for them. That’s when he and Chia decided to go all-in on the idea—and Eventual was born.
What Eventual Is Building
Eventual launched in early 2022, before the rise of ChatGPT and the explosion of generative AI. Their core product is Daft, an open-source, Python-native engine built to process all kinds of data—video, audio, images, text, and more—all in one place.
It’s designed to be fast, flexible, and easy for developers to use.
Think of it like this: SQL changed how we handle structured data like spreadsheets. Eventual wants Daft to do the same for unstructured data.
Why This Matters Now
Since ChatGPT took off, more and more companies have started building AI tools that work with images, documents, voice, and video—not just text. That’s led to a sudden demand for infrastructure that can actually support those formats.
Eventual’s timing couldn’t have been better.
Today, Daft is already being used by teams at:
- Amazon
- CloudKitchens
- Together AI
And it’s gaining traction across industries like:
- Robotics
- Retail technology
- Healthcare
- Autonomous systems
Backed by Big Investors
In less than a year, Eventual raised two funding rounds:
- $7.5M seed round, led by CRV
- $20M Series A, led by Felicis with participation from Microsoft’s M12 and Citi
The new funding will help them grow their open-source platform and launch their first commercial product later this year.
Why Investors Are Paying Attention
Astasia Myers, General Partner at Felicis, discovered Eventual while researching companies solving the data bottleneck in AI.
What stood out?
- The founders had lived the problem themselves at Lyft.
- They were among the first movers in the emerging multimodal AI infrastructure space.
- The market is growing fast — multimodal AI is projected to grow at 35% per year through 2028.
- Most of the data being generated today is unstructured — and Daft is built specifically for that kind of data.
“Daft fits into this huge trend of AI tools working with text, images, video, and voice,” Myers said.
“And Eventual is giving teams the tools they need to keep up.”
In Simple Terms
Here’s why Eventual matters:
- AI models today aren’t just reading text — they’re processing everything.
- Most tools were never designed to handle video, audio, and other messy formats.
- Eventual’s Daft engine helps teams manage all of that unstructured data, without duct-taping tools together.
- The company is growing fast and gaining traction with top tech players.
What’s Next?
Eventual is preparing to roll out an enterprise version of Daft in the coming months. The idea is to give developers and businesses a clean, powerful tool to build smarter AI apps — without getting buried under a mountain of data chaos.
And while the idea started in the world of self-driving cars, it’s clear that the need for tools like Daft is everywhere now.