Youth and passion are a potent combination. Add in drive, grit, and curiosity, and you have the perfect descriptors for this year's **Inno Under 25**, a six-member cohort of next-generation entrepreneurs ready to leave their mark.

![Inno Under 25 Hero Image](https://media.bizj.us/view/img/13075505/inno-under-25-hero-image01*900xx6400-3600-0-0.jpg)

Cincy Inno is recognizing six young entrepreneurs you need to know as part of our annual **Inno Under 25 list**. These rising stars are tackling big challenges and shaping the future of **Cincinnati's startup scene**.

Cincinnati's Inno Under 25 honors young entrepreneurs tackling big challenges. Meet the minds shaping the future of the Queen City's startups.

Meet Cincinnati's Top 6 Young Entrepreneurs Under 25: The Future of Innovation

## The Shift from Quantity to Quality in AI Training Data

For one week this summer, **Taylor and her roommate wore GoPro cameras strapped to their foreheads** as they painted, sculpted, and did household chores. They were training an AI vision model, carefully syncing their footage so the system could get multiple angles on the same behavior. It was difficult work in many ways, but they were well paid for it — and it allowed Taylor to spend most of her day making art.

“We woke up, did our regular routine, and then strapped the cameras on our head and synced the times together,” she said. “Then we would make our breakfast and clean the dishes. Then we’d go our separate ways and work on art.”

They were hired to produce five hours of synced footage each day, but Taylor quickly learned she needed to allot seven hours a day for the work, to leave enough time for breaks and physical recovery.

“It would give you headaches,” she said. “You take it off and there’s just a red square on your forehead.”

Taylor, who asked not to give her last name, was working as a data freelancer for **Turing**, an AI company. Turing’s goal wasn’t to teach the AI how to make oil paintings, but to gain more abstract skills around **sequential problem-solving and visual reasoning**. Unlike a large language model, Turing’s vision model would be trained entirely on video — and most of it would be collected directly by Turing.

Alongside artists like Taylor, Turing is contracting with chefs, construction workers, and electricians — anyone who works with their hands. Turing Chief AGI Officer Sudarshan Sivaraman told TechCrunch the manual collection is the only way to get a varied enough dataset.

“We are doing it for so many different kinds of blue-collar work, so that we have a **diversity of data in the pre-training phase**,” Sivaraman said. “After we capture all this information, the models will be able to understand how a certain task is performed.”

## The Growing Importance of Proprietary Data in AI

Turing’s work on vision models is part of a growing shift in how AI companies deal with data. Where training sets were once scraped freely from the web or collected from low-paid annotators, companies are now **paying top dollar for carefully curated data**.

With the raw power of AI already established, companies are looking to **proprietary training data as a competitive advantage**. And instead of farming out the task to contractors, they’re often taking on the work themselves.

The email company **Fyxer**, which uses AI models to sort emails and draft replies, is one example.

After some early experiments, founder Richard Hollingsworth discovered the best approach was to use an array of small models with tightly focused training data. Unlike Turing, Fyxer is building off someone else’s foundation model — but the underlying insight is the same.

“We realized that the **quality of the data, not the quantity**, is the thing that really defines the performance,” Hollingsworth said.

In practical terms, that meant some unconventional personnel choices. In the early days, Fyxer engineers and managers were sometimes outnumbered four to one by the executive assistants needed to train the model, Hollingsworth says.

“We used a lot of experienced executive assistants, because we needed to train on the fundamentals of whether an email should be responded to,” he said. “It’s a very people-oriented problem. Finding great people is very hard.”

The pace of data collection never slowed down, but over time Hollingsworth became more precious about the datasets, preferring smaller sets of more tightly curated datasets when it came time for post-training. As he puts it, “the quality of the data, not the quantity, is the thing that really defines the performance.”

## The Role of Synthetic Data and Competitive Moats

That’s particularly true when **synthetic data** is used, magnifying both the scope of possible training scenarios and the impact of any flaws in the original dataset. On the vision side, Turing estimates that 75% to 80% of its data is synthetic, extrapolated from the original GoPro videos. But that makes it even more important to keep the original dataset as high-quality as possible.

“If the pre-training data itself is not of good quality, then whatever you do with synthetic data is also not going to be of good quality,” Sivaraman says.

Beyond concerns of quality, there’s a powerful competitive logic behind keeping data collection in-house. For Fyxer, the hard work of data collection is one of the best **moats the company has against competition**. As Hollingsworth sees it, anyone can build an open source model into their product — but not everyone can find expert annotators to train it into a workable product.

“We believe that the best way to do it is through data,” he said, “through building custom models, through high-quality, human-led data training.”

Where training sets were once scraped freely from the web or collected from low-paid annotators, companies are looking to proprietary training data as a competitive advantage.

The Secret Weapon of AI Startups: Why High-Quality Data Collection Is Becoming Their Biggest Competitive Edge

## The AI-Fusion Partnership

Energy startup **Commonwealth Fusion Systems (CFS)** announced it's collaborating with **Google's DeepMind** division to optimize and enhance the operation of its upcoming **Sparc reactor** using artificial intelligence.

![Alex Creely, director of Tokamak operations at Commonwealth Fusion Systems, points to a reactor schematic.](https://s.yimg.com/ny/api/res/1.2/V1ql49hpFEkCInEOSIlJFg--/YXBwaWQ9aGlnaGxhbmRlcjt3PTY0MDtoPTQ1NztjZj13ZWJw/https://media.zenfs.com/en/techcrunch_finance_785/08e270e765192aacaef87dfb9b0d19a8)

*Alex Creely, director of Tokamak operations at Commonwealth Fusion Systems, at the company's campus in Devens, Massachusetts, US, on Wednesday, Nov. 6, 2024. Commonwealth Fusion Systems LLC's growing conviction that fusion is within reach after decades of research comes as the company completes the magnet that will be critical for containing the superheated plasma needed to generate power. | Image Credits:Cassandra Klos/Bloomberg / Getty Images*

## How AI Is Transforming Fusion Energy

The partnership will use DeepMind's specialized software **Torax** to simulate the plasma behavior inside CFS's reactor. The companies plan to combine Torax with **AI models** to identify the most effective approaches for achieving **fusion power**.

**Fusion power** offers the potential for massive electricity generation with **zero emissions** from an almost limitless fuel source: water. This has attracted significant interest from **AI companies** seeking reliable power for energy-intensive data centers.

## Google's Growing Fusion Portfolio

This isn't Google's first venture into nuclear fusion. The tech giant previously worked with another fusion startup, **TAE Technologies**, using AI to study plasma behavior in their fusion device.

Google's continued interest stems from AI's unique capability to solve one of fusion's biggest challenges: maintaining plasma stability. Unlike self-sustaining nuclear fission reactions, **fusion reactions** are extremely difficult to maintain outside stellar conditions. The plasma constantly risks diffusion and extinction without massive gravitational forces.

## The Plasma Control Challenge

In CFS's reactors, powerful magnets replace gravity to contain the plasma, but they're imperfect. Reactor operators must develop **control software** that can continuously adapt to changing plasma conditions.

The complexity lies in the numerous variables involved—far more than humans can manage effectively. This is precisely where **AI excels**, and experts consider it one of the key technologies driving the industry's recent remarkable advances.

## Sparc Reactor Progress

CFS is currently building its **Sparc demonstration reactor** in a Boston suburb. The device is approximately **two-thirds complete** and scheduled for completion in late 2026. The startup predicts Sparc will be the **first fusion device** capable of producing more power than it consumes.

## Advanced AI Applications

Google states that Torax can be integrated with **reinforcement learning** or **evolutionary search models** to identify the most efficient and robust paths to achieving **net energy generation**. The companies are also exploring whether AI can directly control reactor operations.

## Strategic Investments and Partnerships

In August, Google participated in CFS's **$863 million Series B2** funding round alongside **Nvidia**. Earlier this year, Google committed to purchasing **200 megawatts of electricity** from CFS's first commercial power plant, **Arc**, planned for construction outside Richmond, Virginia. Google also maintains investments in CFS competitor TAE Technologies.

Google has invested in fusion startups as potential power suppliers. This latest move suggests Google sees them as potential customers, too.

Google DeepMind's AI Breakthrough Could Finally Make Fusion Power a Reality

## Mississippi's Tech Scene: A New Dawn

Mississippi has long lamented its shortage of **technology startups** and **venture capital**, a challenge dating back to the 1990s dot-com boom. Now, **Innovate Mississippi** is stepping up with a promising solution. Through its **12-week startup accelerator program**, CoBuilders, the nonprofit is providing **funding and training** to seven local tech startups, aiming to spur economic growth and job creation.

### Empowering Entrepreneurs with Guidance and Capital

Take the story of Alex Bucklew and Johnathan McAdory, founders of **SimpleScript**. Their innovative product aggregates prescription drug discounts to find the best prices. As first-time entrepreneurs, they found the accelerator invaluable. "Especially something that's scalable to the level SimpleScript is, it can be difficult to figure out what to do next," Bucklew shared. "We needed some counsel on how to get from point A to point B. From working with CoBuilders, we will be ready to get funding."

Innovate Mississippi, funded by a mix of public and private money, invests **$25,000** into each participating company. This year's cohort is refining their products for a pitch day on November 11, where they aim to raise over **$100,000 each** from investors. Unlike traditional small businesses, these startups focus on **rapid growth** and capturing large market shares, often relying on **angel investors** in their early stages.

### Bridging Gaps in a Nascent Ecosystem

Tony Jeff, CEO and president of Innovate Mississippi, emphasizes the importance of connecting entrepreneurs with resources across the state. "With 3 million people in Mississippi, we've gotta do a lot of work just to find the business that needs the mentor three hours away, that needs the accounting person," Jeff explained. "We connect those dots." Without such support, founders might seek opportunities elsewhere, exacerbating the state's **brain drain**.

Jeff notes that a polished pitch isn't enough; founders must research competitors and gather user feedback. For instance, Leta Palmiter's company, **Vertical Take-Off Reading**, has undergone three pilot rounds and serves over 130 students. Developed with co-founder Ben Stasa, this software measures oral reading skills to aid students, particularly those with dyslexia. "We know that it's doing a great job measuring that accuracy at that sound level, and that kind of data will drive instruction," Palmiter said, highlighting how the tool complements teaching without replacing it.

### Universities and Untapped Potential

Mississippi's colleges are actively supporting the startup pipeline through research funding and idea incubation. Innovate collaborates with universities to host pitch competitions and connect with founders. Ricky Romanek, founder of **ClaimTra**, a healthcare analytics tool for insurance claim recovery, acknowledged this: "There's a lot of resources that the schools and universities help support tech entrepreneurs."

Romanek believes Mississippi holds **huge untapped startup potential**. "I think there's a huge startup potential in Mississippi that's untapped. There's a lot of great ideas. I don't think they're aware of all the resources that are available," he remarked. Jeff echoes this, seeing the tech sector as a key to retaining talent and addressing job shortages, noting that students often consider leaving due to limited opportunities.

### The Path Forward

Identifying the right companies for the accelerator is crucial—they must be innovative, early-stage, and high-growth. "It is very obvious we have more money chasing deals than we have deals. So we've got to get everything we can to make every startup qualified for that money," Jeff stated. Innovate's role in nurturing home-grown businesses and attracting new ventures could redefine Mississippi's economic landscape, turning nascent ideas into thriving enterprises.

Mississippi has a nascent tech scene and state leaders have struggled with how to grow it, but Innovate Mississippi believes it might have a solution.

How Mississippi's Startup Accelerator Is Fueling a Tech Revolution and Creating Jobs

## Deel's Monumental Funding Round

Payroll startup **Deel** announced on Thursday that it has raised **$300 million** in a Series E funding round, catapulting its valuation to an impressive **$17.3 billion**. The round was led by new investor **Ribbit Capital**, with continued support from existing backers **Andreessen Horowitz** and **Coatue Management**.

## Strategic Expansion Plans

Based in San Francisco, California, Deel plans to utilize this fresh capital for strategic **acquisitions** and to significantly expand its **payroll infrastructure**. The company has set an ambitious goal to offer **native payroll services in over 100 countries by 2029**, reinforcing its commitment to global growth.

## Intense Rivalry and Legal Battles

This funding milestone comes amidst ongoing litigation with rival **Rippling**. Rippling has sued Deel, alleging **racketeering, trade-secret misappropriation, and unfair competition**. In response, Deel filed a defamation suit against Rippling in April, dismissing the claims as a "multi-year smear campaign." Deel CEO Alex Bouaziz declined to comment on the litigation but labeled it a "frivolous lawsuit."

Earlier this year, Rippling raised **$450 million in a Series G funding round**, valuing the company at **$16.8 billion**, highlighting the competitive tension in the HR tech space.

## Financial Performance and Growth Metrics

Bouaziz revealed that Deel crossed **$100 million in monthly revenue for the first time in September**, with earnings before interest, taxes, depreciation, and amortization (EBITDA) ranging between **$15 million and $17 million**. Founded in 2019, Deel specializes in helping companies hire international employees and contractors while ensuring compliance with local labor laws, and automates payroll processing for businesses operating across multiple countries.

## Previous Valuation and Acquisitions

Deel was previously valued at **$12.6 billion** after a $300 million secondary purchase by General Catalyst and Abu Dhabi's Mubadala earlier this year. The company recently acquired its London-based competitor **Omnipresent** in a deal worth approximately **$15 million**, according to a source familiar with the matter.

Deel had already crossed the **$1 billion annual revenue run rate** in the first quarter and had earmarked up to **$500 million for acquisitions this year** to bolster growth, as previously stated.

Payroll startup Deel said on Thursday it raised $300 million in a funding round, led by new investor Ribbit Capital alongside existing backers Andreessen Horowitz and Coatue Management, valuing the company at $17.3 billion.

Deel Soars to $17.3 Billion Valuation with $300M Funding, Fueling Global Expansion and Rivalry with Rippling

Many ad tech veterans who previously dabbled in the startup life keep coming back to it. And with an AI bubble **17 times the size** of the dot-com bubble, it looks like an ad tech-to-AI pipeline is beginning to form.

As AI sinks its teeth into every aspect of the tech world, from media buying to search, more and more ad execs are leaving their c-suite jobs, following their entrepreneurial instincts and launching their own AI startups.

Many of these founders worked in tech in the early days of the internet, and, they say, the dawn of AI is similarly scary, novel and unpredictable. But most of all, it’s exciting.

We spoke to seven ad tech vets about their forays into AI, and what set them on this path.

## Jonathan Moffie, Streamr.ai

Jonathan Moffie’s history in ad tech is somewhat reminiscent of a Russian nesting doll. He started within larger companies and shifted to smaller and smaller ones, until he reached the center: his own startup.

Founded in 2024 by Moffie, Frank Turano (a former engineer at Shutterstock and Dotdash Merideth) and Burhan Hamid (former CTO of TIME), Streamr was established to make **CTV advertising faster and more affordable for SMBs**. In September, it was acquired by Magnite.

From 2022 to 2023, Moffie was head of product at streaming video distribution platform Wurl, before shifting to a small startup called Orka until mid-2024. Orka’s goal, Moffie said, was the same as Streamr’s: “to build the easiest way to advertise on TV.” Back then, he said, it was a lengthy process – and not a cheap one, either.

Streamr was born out of the belief that advertising on CTV can be done with any budget and in practically no time.

An advertiser just has to input its business name or website, said Moffie, and within a couple of minutes, the platform scrapes the site and online reviews and pulls relevant images and content to generate a commercial.

Within minutes, he said, the advertiser can hit “launch on TV” and, once approved by the streaming service, the ad goes live.

Moffie said his experience on smaller teams and working directly with other entrepreneurs is how he learned best practices for building his own startup.

“I made a concerted effort to join a startup” to learn from “people who had done it before,” he said.

## Joe Luchs, Datalinx AI

Joe Luchs’ career has run the gamut of ad tech. He’s seen it all, from early-stage startups like Beeswax (which he helped to found) to what he called the “massive titans” like Amazon (where he served most recently as global head of AWS and Amazon Ads).

His latest project is Datalinx AI, which he described as an “**AI data refinery**” that takes raw, messy data and organizes it into “fuel” that companies can use, like clearly labeled and normalized datasets. Datalinx was co-founded by Luchs, Jeff Collins, Nicole Landis Ferragonio and Alek Liskov, who met through a mix of business school, AI-focused industry events and mutual friends.

A lot of companies have a whole lot of data but not in a form that they can easily access or garner insights from. It’s like if you bought a new car, said Luchs, but when you showed up to the gas station to fill the tank, you were told, “Hey, you need to drill into the ground, extract the fuel, refine the fuel, put it into the pump, then you can put it into your car and *then* you can go for a cool ride.”

Datalinx developed a team of specialized AI agents to complete tasks ranging from scanning a cloud database and processing datasets to identity resolution.

Each agent is powered by a series of LLMs, including OpenAI, Anthropic, AWS and Meta.

It’s a “very sexy solution,” he said, “to a very unsexy problem.”

## Frans Vermeulen, Swivel

Swivel’s goal is to **automate the entire ad operations process**, from selling media to tracking campaigns to providing analytics and reporting, said President and Co-Founder Frans Vermeulen.

Vermeulen founded the platform with SpringServe co-founders Joe Hirsch, Matt Dearborn and Rich Lin. While “it’s still ad tech, and it’s still operations,” it’s “the most exciting thing [I’ve] ever worked on,” Vermeulen said.

Programmatic was designed to entirely automate digital media trading, and it did. But in doing so, it introduced new “operational burdens” that require humans to run and analyze reports – repetitive tasks, that could be solved with a “rules-based piece of software,” he said.

In addition to being repetitive, ad ops can also be frustratingly complex for marketers and publishers – the latter of which compose most of Swivel’s current client base.

Clients first have a consultation with Swivel to determine their goals. The company then selects a couple of use cases that it believes it can solve “right out the gate” to demonstrate Swivel’s ability to automate and replicate human behavior at scale, Vermeulen said.

This can look like anything from changing price floors or frequency capping to having varying strategies at different times of day, based on shifting demand patterns.

The platform makes “tens of thousands of micro-adjustments per day,” said Vermeulen, executing changes in “one fell swoop” that would take days for a human team.

“Humans are just naturally limited by the fact that we’re human,” he said.

Much to consider.

## Michael Rubenstein, Firsthand

The “choose-your-own-adventure” format has come up in nearly every form of media, from video games to full-length novels and even that one episode of Black Mirror.

It only makes sense that ad tech would be next in line.

Firsthand, which markets itself as an AI-powered **brand agent platform**, is effectively a choose-your-own-adventure ad experience for consumers.

Brand agents serve as virtual brand reps who have knowledge of both a brand’s goals and individual consumers’ preferences, said Michael Rubenstein, co-founder and co-CEO of Firsthand. Those agents “guide consumers through a totally personalized, one-to-one journey.”

The AI agents process and understand content on a publisher’s site and tailor relevant brands’ ads to readers, with different product suggestions for viewers to choose from. For example, Firsthand’s agents might determine that a certain webpage is likely to reach consumers who have an interest in beauty products, so it would serve an ad for a beauty brand. But instead of standard contextual targeting, the ad would have multiple products to choose from, allowing the viewer to select the best fit depending on whether they’re familiar with the industry, curious about new products or shopping on a budget.

Once the viewer selects an option, they’re shown more pre-approved content from the brand with product information and recommendations on how to use it.

Rubenstein co-founded the platform with Jonathan Heller, with whom he worked at DoubleClick, and Wei Wei, Heller’s colleague at FreeWheel. (The circle of ad tech…)

“We love to build,” said Rubenstein, and “one of the biggest challenges in this new AI era is [determining how] brands survive and thrive.” They shouldn’t just be on the receiving end of AI, he added, but “users and beneficiaries” themselves.

Solving that problem with a brand agent platform, he said, is “the most interesting, exciting and important thing that we could be spending our time on.”

## Rory Partalis, Classify

When Rory Partalis worked as Pandora’s ad product marketing manager in the early 2010s, he was fascinated by the platform’s Music Genome Project, which matches songs to an individual user’s tastes.

He later became VP of product at Partpic Inc., a startup that used computer vision and AI to help customers find missing parts of industrial products. Customers sent in photos of their products and the company, which was acquired by Amazon in 2016 and has since become defunct, determined the exact replacement needed.

“AI has kind of been sprinkled throughout the last decade or so of my career,” said Partalis.

So perhaps it was inevitable that his next step would be to found his own AI startup. Partalis launched Classify earlier this year, with co-founders Brendan Norman, a former Facebook exec and Nick Ross, the director of University of Chicago’s AI and machine learning data science clinic.

Classify’s “grand vision,” as Partalis described it, is to **classify and contextualize all monetizable web pages** across the internet. The tool scans over two billion web pages and pulls the content into its platform for categorization.

“We’re big on AI-first vibe targeting,” said Partalis. Advertisers can submit a single prompt and Classify will return relevant and high-performing content by understanding “what the customer is trying to target, who they’re trying to target, what their product is [and] what their goals are.”

Ultimately, Classify aims to help marketers advertise on relevant content and publishers package their inventory into curated deals.

The contextual targeting industry is built on “outdated taxonomies and categories and keywords,” said Partalis. More modern technologies, like AI, can look at a URL and scan a website in its entirety for a better understanding of the content.

Now, he said, is the “right point in time for privacy and AI to coincide and build something new.”

## Joe Prusz, Medialive

Media buying has never been a simple process.

Medialive’s founding team set out to change that using – what else – AI.

A marketplace needs to serve both sides, said Joe Prusz, who recently joined the company as CEO and co-founder, and the goal behind Medialive was to “create a place for buyers, sellers and vendors to collaborate.”

(Prusz was formerly CRO of Magnite, and his co-founder Adrien Passerieux spent years working in sales and SaaS at Google. Prusz describes their collaboration as a “wonderful example of the buy side and sell side coming together to tackle a systemic industry problem that has plagued us all for far too long.”)

Medialive is like **Slack or Whatsapp for media buying**, Prusz said – a single room where everyone in the media buying chain, from the advertisers to the DSPs and SSPs to the publishers, can communicate directly.

At its core, it’s a straightforward system.

First, an advertiser uploads a brief into one of the digital rooms and invites other participants into the room who can converse and negotiate. Then, all parties can see the tech set up on both the buy side and the sell side. Medialive’s technology interfaces with APIs that pull in data from platforms including DV360, The Trade Desk and Magnite.

Medialive’s AI reads and summarizes the chat room in real time, said Prusz, and churns out a to-do list for the advertiser, from fixing geographic targeting errors to supplying missing inventory that could aid the campaign.

After spending over a decade at Rubicon Project (the artist currently known as Magnite), most recently as CRO, Prusz said he needed to build something from scratch. “That was really the entrepreneur in me,” he said. From there, he joined Hoppr, a small startup CTV platform, as CEO.

Prusz has seen the same problems across tech platforms for the past twenty years, he said: “broken workflows, the inability for humans to communicate effectively, mistakes on the front end that flow all the way through to the back end and create a wake of destruction for everyone.”

“We’ve lived these problems,” he said. And Medialive is trying to address them “all together in one solution.”

## Kyle Csik, Adaly

It’s a pretty bold claim, but Kyle Csik believes his team has built “**the Spotify of data**.”

Instead of downloading data piecemeal and compiling it into a cohesive “playlist,” Adaly, co-founded by CEO Csik and CTO Aleksandar Sasha Grujicic, pulls in real-time data from all of a marketer’s sources. The company uses data from sources like Google Analytics, Statista and the Trade Desk to produces analytics and reports without any downloads or data infrastructure.

LLMs function as the brain of the system, Csik said: They can “think” and reason and connect disparate ideas. Adaly, on the other hand, he views as the nervous system, allowing the LLM to move in and out of ad tech and martech platforms. “Any model, any piece of data and any AI agent can be orchestrated in real time,” he said.

“The best use case,” Csik said, is asking Adaly to compare an advertiser’s own sales results to its competitors. Adaly will go into whatever platform an advertiser uses to track its own data, like Google analytics, and compare that against other sources like Circana data, churning out real-time comparisons and analyses.

This isn’t Csik’s first foray into automation. He’s worked at major holdcos and ad tech companies, including Publicis and GroupM, where the goal was always to develop new infrastructure and improve UI. Although, he thinks improving UI will become less of a focus as systems become more “destination-less” through APIs and natural language prompting.

Instead of requiring people to seek out a particular system, we should be bringing the system to them, Csik said. Adaly’s customers don’t need to go to the company’s website to use the tool, he said; they can call into the system directly from their phone, similar to how Siri works within Apple products.

Csik hopes that as more traditional UIs fade away in favor of natural language prompting, the quality of research and execution that Adaly provides will keep it afloat.

“I’ve built a career out of automating myself out of a job,” he said.

As AI sweeps the tech landscape, new startups keep emerging. Here are seven former ad tech execs' thoughts on best AI practices and starting their own companies.

From Ad Tech Titans to AI Trailblazers: 7 Visionaries Building the Future of Advertising

Indian quick-commerce startup **Zepto** has secured a massive $400 million in funding, led by the **California Public Employees’ Retirement System (CalPERS)**, a U.S.-based pension fund. This round, a mix of primary and secondary investment, includes participation from existing backers like **Avenir, Avra, Lightspeed, Glade Brook, The Stepstone Group, and Nexus Venture Partners**. Following this injection, Zepto is gearing up for an IPO next year.

Zepto operates in a fiercely competitive landscape, going head-to-head with giants like **Eternal’s BlinkIt, Swiggy Instamart, and Tata-owned BigBasket**—all under publicly listed umbrellas. The startup has been on a funding tear, raising **$1.3 billion in just a few months last year**. Since its last round in November 2024, the market has shifted dramatically: Swiggy went public, and BlinkIt overtook Zomato in gross order value for Q1 2025.

Legacy e-commerce titans are also entering the fray, with **Flipkart and Amazon** launching their own quick-commerce services to capture the booming demand.

Beyond groceries, startups are diversifying into verticalized e-commerce. **Accel-backed Swish** and Zing focus on food delivery; **Nykaa, Myntra, Silkk, and Blip** aim for one-hour apparel delivery; **Lightspeed-backed Snabbit** offers home services like cleaning in under 10 minutes; and **FirstClub** takes a curated approach to grocery delivery.

Zepto's CEO, **Aadit Palicha**, is bullish on growth, noting a surge from 500,000 daily orders five quarters ago to **1.7 million daily orders** today. He emphasized that the funding was driven by achieving profitability in dark stores while adding over **10 million new monthly transacting users**. Despite pausing its Zepto Cafe in 44 cities due to staffing issues, the service has rebounded to a **$110 million run rate** and is expanding fast.

Market forecasts are overwhelmingly positive: **Morgan Stanley** projects India's quick-commerce sector could hit **$42 billion by 2030**, while **Bernstein** sees it reaching **$100 billion in a decade**, with quick commerce becoming the primary grocery shopping method in target areas.

Zepto's expansion is concentrated in major cities, with over **1,000 stores across 80+ cities**, compared to BlinkIt's 204+ and Swiggy Instamart's 104+. The startup plans to add hundreds more stores in the next year and is seeing nearly **20% of orders from smaller cities**, signaling broader adoption.

The app features offerings like **Super Saver** for bulk grocery discounts and categories like electronics and fashion, but Palicha admits the interface is cluttered and promises simplifications soon.

CalPERS' investment marks a strategic shift, as the pension fund typically avoids direct startup bets. Since 2022, it has aggressively scaled its venture allocation from $800 million to a targeted $5 billion, indicating strong confidence in India's quick-commerce sector and a growing appetite for direct investments in emerging markets. CalPERS also backs funds of Zepto's investors, such as Lightspeed and General Catalyst.

Indian quick-commerce startup Zepto said it has raised $400 million in a funding round led by a new investor, the California Public Employees’ Retirement System (CalPERS), a U.S.-based pension fund.

Zepto's $450M Mega-Round Fuels India's Explosive Quick-Commerce Revolution

## Kuku's Strategic Expansion in India's Booming Digital Market

**Kuku**, an Indian storytelling platform backed by Google, has secured **$85 million** in Series C funding to scale its audio and video content offerings. This round, led by **Granite Asia**, values the startup at over **$500 million**—more than double its previous valuation. Other investors include Vertex Growth Fund, Krafton, IFC, Paramark, Tribe Capital India, and Bitkraft.

### Key Growth Drivers in India

India's digital content market is exploding, with over a billion internet subscribers and 700 million smartphone users. Ultra-low data costs—where **1GB costs less than a cup of tea**—and the government-backed **Unified Payments Interface (UPI)** have made digital transactions seamless. In 2024, digital media overtook television for the first time, contributing **32% of India's media and entertainment revenues** (₹802 billion, ~$9.13 billion). The sector is projected to grow at a **CAGR of 11.2% from 2024 to 2027**.

### Kuku's Platform Evolution

Founded in 2018, Kuku initially gained traction with **audiobook offerings** through **Kuku FM**. It has since expanded to include:
- **Kuku TV**: Long-form stories in bite-sized vertical episodes
- **Kuku FM**: Audio-first shows
- **Kuku Bhakti**: Devotional content based on Hindu mythology
- **StoRizz**: Microdramas—short, serialized video stories

Content is available in **over eight Indian languages**, and the platform has surpassed **10 million paid subscribers** (up from 2 million in 2023).

### User Engagement and Monetization

- **Average daily usage**: 100 minutes per user
- **Over 90% monthly active retention**
- Subscription plans: ₹199/month (~$2), ₹499/quarter (~$6), ₹1,499/year (~$17)—with the quarterly plan being most popular
- **80% of subscribers from non-metropolitan cities**
- Demographic split: 60% male, 40% female, mostly aged 25-35

### Content Creation and AI Integration

Kuku works with **~10,000 creators**, over 50% from small towns, paying **~₹400 million monthly (~$4.5 million)**. The startup has built a **GenAI studio** using tools from OpenAI, ElevenLabs, and in-house solutions to assist creators with titles, plots, scripts, dialogues, and thumbnails. **70-80% of Kuku's work is powered by GenAI**, though actual audio/video production remains manual.

### Competitive Landscape and Legal Challenges

Kuku faces stiff competition from **Pocket FM**, which has filed multiple copyright infringement lawsuits. The Delhi High Court recently restrained Kuku from releasing new episodes of five disputed shows. Kuku claims these lawsuits are timed to distract investors during fundraises and has developed tools to detect copyright violations.

### Performance Metrics

- **Total downloads**: 229+ million (122M for Kuku FM, 88M for Kuku TV)
- **Consumer spending**: Over $4 million ($2.8M from Kuku FM, $1.3M from Kuku TV)
- **2025 growth**: 134M downloads (533% YoY increase), $1.9M consumer spending (156% YoY increase)
- **Kuku TV accounts for over 60% of total usage**

### Future Plans

The new funding will be used to:
- Enhance AI and data infrastructure
- Expand the 150-person workforce
- Deepen creator partnerships
- Scale in India and beyond, with **U.S. launch planned for 2026** and current testing in the Middle East

![Kuku vs Pocket FM comparison](https://techcrunch.com/wp-content/uploads/2025/10/kuku-pocket-fm_428a81.jpg)

Kuku plans to expand beyond India with a U.S. launch slated for next year.

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