Technology
How a data processing problem at Lyft became the basis for Eventual

When Eventual founders Sammy Sidhu and Jay Chia were working as software engineers at Lyft’s autonomous vehicle program, they witnessed a brewing data infrastructure problem — and one that would only become larger with the rise of AI.
Self-driving cars produce a ton of unstructured data from 3D scans and photos to text and audio. There wasn’t a tool for Lyft engineers to that could understand and process all of those different types of data at the same time — and all in one place. This left engineers to piece together open source tools in a lengthy process with reliability issues.
“We had all these brilliant PhDs, brilliant folks across the industry, working on autonomous vehicles but they’re spending like 80% of their time working on infrastructure rather than building their core application,” Sidhu, who is Eventual’s CEO, told TechCrunch in a recent interview. “And most of these problems that they were facing were around data infrastructure.”
Sidhu and Chia helped build an internal multimodal data processing tool for Lyft. When Sidhu set out to apply to other jobs, he found interviewers kept asking him about potentially building the same data solution for their companies, and the idea behind Eventual was born.
Eventual built a Python-native open source data processing engine, known as Daft, that is designed to work quickly across different modals from text to audio and video, and more. Sidhu said the goal is to make Daft as transformational to unstructured data infrastructure as SQL was to tabular datasets in the past.
The company was founded in early 2022, nearly a year before ChatGPT was released, and before many people were aware of this data infrastructure gap. They launched the first open source version of Daft in 2022 and are gearing up to launch an enterprise product in the third quarter.
“The explosion of ChatGPT, what we saw is just a lot of other folks who are then building AI applications with different types of modalities,” Sidhu said. “Then everyone started kind of like using things like images and documents and videos in their applications. And that’s kind of where we saw, usage just increased dramatically.”
While the original idea behind building Daft stemmed from the autonomous vehicle space, there are numerous other industries that process multimodal data, including robotics, retail tech, and healthcare. The company now counts Amazon, CloudKitchens and Together AI, among others, as customers.
Eventual recently raised two rounds of funding within eight months. The first was a $7.5 million seed round led by CRV. More recently, the company raised a $20 million Series A round led by Felicis with participation from Microsoft’s M12 and Citi.
This latest round will go toward bulking up Eventual’s open source offering as well as creating a commercial product that will allow its customers to build AI applications off of this processed data.
Astasia Myers, a general partner at Felicis, told TechCrunch that she found Eventual through a market mapping exercise that involved looking for data infrastructure that would be able to support the growing number of multimodal AI models.
Myers said that Eventual stood out for being a first mover in the space — which will likely get more crowded — and based on the fact that the founders had dealt with this data processing problem firsthand. She added that Eventual is also solving a growing problem.
The multimodal AI industry is predicted to grow at a 35% compound annual growth rate between 2023 and 2028, according to management consulting firm MarketsandMarkets.
“Annual data generation is up 1,000x over the past 20 years and 90% of the world’s data was generated in the past two years, and according to IDC, the vast majority of data is unstructured,” Myers said. “Daft fits into this huge macro trend of generative AI being built around text, image, video, and voice. You need a multimodal-native data processing engine.”
Technology
Pintarnya raises $16.7M to power jobs and financial services in Indonesia

Pintarnya, an Indonesian employment platform that goes beyond job matching by offering financial services along with full-time and side-gig opportunities, said it has raised a $16.7 million Series A round.
The funding was led by Square Peg with participation from existing investors Vertex Venture Southeast Asia & India and East Ventures.
Ghirish Pokardas, Nelly Nurmalasari, and Henry Hendrawan founded Pintarnya in 2022 to tackle two of the biggest challenges Indonesians face daily: earning enough and borrowing responsibly.
“Traditionally, mass workers in Indonesia find jobs offline through job fairs or word of mouth, with employers buried in paper applications and candidates rarely hearing back. For borrowing, their options are often limited to family/friend or predatory lenders with harsh collection practices,” Henry Hendrawan, co-founder of Pintarnya, told TechCrunch. “We digitize job matching with AI to make hiring faster and we provide workers with safer, healthier lending options — designed around what they can reasonably afford, rather than pushing them deeper into debt.”
Around 59% of Indonesia’s 150 million workforce is employed in the informal sector, highlighting the difficulties these workers encounter in accessing formal financial services because they lack verifiable income and official employment documentation.
Pintarnya tackles this challenge by partnering with asset-backed lenders to offer secured loans, using collateral such as gold, electronics, or vehicles, Hendrawan added.
Since its seed funding in 2022, the platform currently serves over 10 million job seeker users and 40,000 employers nationwide. Its revenue has increased almost fivefold year-over-year and expects to reach break-even by the end of the year, Hendrawn noted. Pintarnya primarily serves users aged 21 to 40, most of whom have a high school education or a diploma below university level. The startup aims to focus on this underserved segment, given the large population of blue-collar and informal workers in Indonesia.
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“Through the journey of building employment services, we discovered that our users needed more than just jobs — they needed access to financial services that traditional banks couldn’t provide,” said Hendrawan. “We digitize job matching with AI to make hiring faster and we provide workers with safer, healthier lending options — designed around what they can reasonably afford, rather than pushing them deeper into debt.”

While Indonesia already has job platforms like JobStreet, Kalibrr, and Glints, these primarily cater to white-collar roles, which represent only a small portion of the workforce, according to Hendrawan. Pintarnya’s platform is designed specifically for blue-collar workers, offering tailored experiences such as quick-apply options for walk-in interviews, affordable e-learning on relevant skills, in-app opportunities for supplemental income, and seamless connections to financial services like loans.
The same trend is evident in Indonesia’s fintech sector, which similarly caters to white-collar or upper-middle-class consumers. Conventional credit scoring models for loans, which rely on steady monthly income and bank account activity, often leave blue-collar workers overlooked by existing fintech providers, Hendrawan explained.
When asked about which fintech services are most in demand, Hendrawan mentioned, “Given their employment status, lending is the most in-demand financial service for Pintarnya’s users today. We are planning to ‘graduate’ them to micro-savings and investments down the road through innovative products with our partners.”
The new funding will enable Pintarnya to strengthen its platform technology and broaden its financial service offerings through strategic partnerships. With most Indonesian workers employed in blue-collar and informal sectors, the co-founders see substantial growth opportunities in the local market. Leveraging their extensive experience in managing businesses across Southeast Asia, they are also open to exploring regional expansion when the timing is right.
“Our vision is for Pintarnya to be the everyday companion that empowers Indonesians to not only make ends meet today, but also plan, grow, and upgrade their lives tomorrow … In five years, we see Pintarnya as the go-to super app for Indonesia’s workers, not just for earning income, but as a trusted partner throughout their life journey,” Hendrawan said. “We want to be the first stop when someone is looking for work, a place that helps them upgrade their skills, and a reliable guide as they make financial decisions.”
Technology
OpenAI warns against SPVs and other ‘unauthorized’ investments

In a new blog post, OpenAI warns against “unauthorized opportunities to gain exposure to OpenAI through a variety of means,” including special purpose vehicles, known as SPVs.
“We urge you to be careful if you are contacted by a firm that purports to have access to OpenAI, including through the sale of an SPV interest with exposure to OpenAI equity,” the company writes. The blog post acknowledges that “not every offer of OpenAI equity […] is problematic” but says firms may be “attempting to circumvent our transfer restrictions.”
“If so, the sale will not be recognized and carry no economic value to you,” OpenAI says.
Investors have increasingly used SPVs (which pool money for one-off investments) as a way to buy into hot AI startups, prompting other VCs to criticize them as a vehicle for “tourist chumps.”
Business Insider reports that OpenAI isn’t the only major AI company looking to crack down on SPVs, with Anthropic reportedly telling Menlo Ventures it must use its own capital, not an SPV, to invest in an upcoming round.
Technology
Meta partners with Midjourney on AI image and video models

Meta is partnering with Midjourney to license the startup’s AI image and video generation technology, Meta Chief AI Officer Alexandr Wang announced Friday in a post on Threads. Wang says Meta’s research teams will collaborate with Midjourney to bring its technology into future AI models and products.
“To ensure Meta is able to deliver the best possible products for people it will require taking an all-of-the-above approach,” Wang said. “This means world-class talent, ambitious compute roadmap, and working with the best players across the industry.”
The Midjourney partnership could help Meta develop products that compete with industry-leading AI image and video models, such as OpenAI’s Sora, Black Forest Lab’s Flux, and Google’s Veo. Last year, Meta rolled out its own AI image generation tool, Imagine, into several of its products, including Facebook, Instagram, and Messenger. Meta also has an AI video generation tool, Movie Gen, that allows users to create videos from prompts.
The licensing agreement with Midjourney marks Meta’s latest deal to get ahead in the AI race. Earlier this year, CEO Mark Zuckerberg went on a hiring spree for AI talent, offering some researchers compensation packages worth upwards of $100 million. The social media giant also invested $14 billion in Scale AI, and acquired the AI voice startup Play AI.
Meta has held talks with several other leading AI labs about other acquisitions, and Zuckerberg even spoke with Elon Musk about joining his $97 billion takeover bid of OpenAI (Meta ultimately did not join the offer, and OpenAI denied Musk’s bid).
While the terms of Meta’s deal with Midjourney remain unknown, the startup’s CEO, David Holz, said in a post on X that his company remains independent with no investors; Midjourney is one of the few leading AI model developers that has never taken on outside funding. At one point, Meta talked with Midjourney about acquiring the startup, according to Upstarts Media.
Midjourney was founded in 2022 and quickly became a leader in the AI image generation space for its realistic, unique style. By 2023, the startup was reportedly on pace to generate $200 million in revenue. The startup sells subscriptions starting at $10 per month. It offers pricier tiers, which offer more AI image generations, that cost as much as $120 per month. In June, the startup released its first AI video model, V1.
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Meta’s partnership with Midjourney comes just two months after the startup was sued by Disney and Universal, alleging that it trained AI image models on copyrighted works. Several AI model developers — including Meta — face similar allegations from copyright holders, however, recent court cases pertaining to AI training data have sided with tech companies.
Got a sensitive tip or confidential documents? We’re reporting on the inner workings of the AI industry — from the companies shaping its future to the people impacted by their decisions. Reach out to Rebecca Bellan at [email protected] and Maxwell Zeff at [email protected]. For secure communication, you can contact us via Signal at @rebeccabellan.491 and @mzeff.88.
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