• Tiun has secured a $2.5 million pre-seed funding round to innovate media monetization.
• The startup offers a pay-for-what-you-use model to reduce friction for media consumers.
• Business Insider got an exclusive look at the 9-slide deck it used to raise fresh funding.

Zurich-based startup Tiun has raised $2.5 million in pre-seed funding for its digital wallet, which lets users pay only for the online media they consume and provides businesses with an alternative way to monetize their content.

The startup aims to streamline the online subscription process, which its cofounder and CCO Nikolaos Christoforakos says is "full of friction" — from registering and authorizing an account to committing to an upfront subscription.

"Our mission is to help media providers — and more broadly service providers — to attract, engage, and convert younger audiences," Christoforakos told Business Insider.

Instead of subscribing to multiple individual media providers, Tiun offers users a digital wallet they can use across multiple media partners to purchase preferred content on a "pay-for-what-you-use" basis.

The account is free to create, with users topping up funds using an established payment method. This eliminates the need to enter new payment details for every outlet and eases the friction in the consumer journey, Christoforakos said.

Tiun gets a slice of each transaction, splitting the rest with the media provider. Companies providing the content — from podcasts to streaming to online news — can also access Tiun's business suite with metrics on reader data and conversions.

"There's a value to the product outside of the infrastructure, and on top of that, we make money with a revenue share," Christoforakos told BI.

Media organizations have been exploring micropayment models for several years — but with limited success. Dutch online news platform Blendle, one of the main champions of micropayments, later ditched its model in favor of subscriptions. Christoforakos says that Tiun is not positioning itself as a micropayment service that's in competition with previous efforts.

But the startup is providing the infrastructure that addresses one of the oft-cited reasons for the micropayment model's slow adoption: the lack of a standard payment method across media outlets.

"Our vision is to redefine how the next generation will consume and pay for online content by establishing a new standard that improves interoperability between wallets and applications," Christoforakos said.

Tiun's funding round was led by Swiss VC firm Founderful, with additional funds coming from Blue Wire Capital and a16z scout Maximilian Lehmann, among other angel investors.

With the fresh funding, Tiun will develop some core product offerings in the coming year.

We got an exclusive look at the 9-slide pitch deck used to secure the fresh funding.

• Nscale has raised $155 million in Series A funding for its hyperscaler platform.
• The startup offers everything from access to data centers to GPU infrastructure.
• BI got an exclusive look at the pitch memo the startup used to secure the fresh funds.

Nscale, a London-based startup providing companies with access to data centers and clusters of AI chips, has raised $155 million in fresh funding.

The startup, which came out of stealth in May 2024, bills itself as a fully integrated AI infrastructure platform.

As a hyperscaler, Nscale provides the "full stack" of technologies companies need to train and run AI applications like large language models. That includes data centers, software, and graphics processing units, Nscale's founder and CEO Joshua Payne told Business Insider in an interview.

The startup differentiates itself from AI cloud providers, such as Lambda Labs and Coreweave, which offer only specific components, such as GPUs, in the AI infrastructure layer. By providing everything from its own data centers to virtualized GPU nodes, Payne said that the company could leverage better unit economics than its competitors.

"The problem for the industry is chicken and egg. Take an LLM customer — they may want 10,000 GPUs, but they don't have the expertise for that," he told BI. "Many of our competitors don't own their own data centers, so they have to license them. In our case, we have all of that in-house. Given that we are able to own all those segments in the value chain, we're faster and cheaper."

Payne said that Nscale pivoted to focus on AI infrastructure across the full stack after the public release of ChatGPT-3. "So our thesis was, if this is indeed the fourth industrial revolution as people are claiming, then how would you build a resilient AI cloud that would survive commodity cycles? said Payne. "We found the best way to do that was to vertically integrate it, building both data centers, GPUs, and software."

Since it emerged from stealth, it has rapidly grown its pipeline of greenfield data center capacity across Europe and the US from 300 megawatts to 1.3 gigawatts.

The startup makes its money by building data centers, purchasing GPUs, and deploying AI cloud services, which it then leases on an hourly basis. Clients can sign contracts for any given period of time to use the services.

Sandton Capital Partners led the $155 million round, which also included participation from Kestrel, Bluesky Asset Management, and Florence Capital. The startup previously raised more than $30 million in pre-seed and seed funding, with the size of those early-stage rounds reflecting investors' heightened appetite to back startups operating in the AI infrastructure layer.

With the fresh funding, Nscale plans to invest in large clusters of GPUs and also double down on software development for its public cloud platform, which will be released in January 2025.

BI got an exclusive look at the 9-slide memo the startup used to secure fresh funding.

• Reflexivity is a startup cofounded by two former hedge fund traders.
• It sells software to hedge funds and institutional investors to speed up the research process.
• The 4-year-old upstart just raised its $30 million Series B.

A startup looking to transform how investors and traders use data just received funding from some of the biggest names in the hedge fund world.

Reflexivity, formerly known as Toggle AI, raised its $30 million Series B in late October. Interactive Brokers and Greycroft led the round, which included participation from billionaire investor Stanley Druckenmiller and Greg Coffey, the Australian founder of hedge fund Kirkoswald. Existing investors include Millennium Management's founder, Izzy Englander, and General Catalyst.

Reflexivity was founded by two former hedge fund traders who were all too familiar with the woes of wrangling disparate data sets to find an investing edge, or at the very least, to not miss out on an opportunity others are seizing. The startup aims to mitigate that by combining third-party data from a dozen providers like S&P Global and newsfeeds, in addition to proprietary internal information, for a full-view analysis and also flagging the potential impact world and market events may have on a portfolio.

"When you are an investor inside a major hedge fund, one big fear that is always present is that you are going to miss something," cofounder and CEO Jan Szilagyi told BI. "It's always exciting to have a trade that you are the only one that's in it, but the thing that is far worse is to miss on the trade that everybody else but you is in."

The four-year-old startup recently changed its name to more closely align with how the platform helps with the investment process, Szilagyi told Business Insider.

"Reflexivity is the act of examining one's own assumptions, beliefs, and judgment systems, and thinking carefully and critically about how these influence the research process," he said, referring to a term popularized by legendary investor George Soros.

Szilagyi was a portfolio manager for nearly 20 years at firms including Druckenmiller's Duquesne Capital Management and Fortress Investment Group. The fintech's president and other cofounder, Giuseppe Sette, also worked in asset management including a stint at macro giant Brevan Howard. They remember the investment analysis process as one that "seemed hopelessly broken" because critical data sources were fragmented and spread out across different providers and systems, Szilagyi said.

The firm estimates the potential market for its services is $16.4 billion. Reflexivity so far has about 20 institutional clients, tallying some 15,000 individual users. Clients include trading platforms like Interactive Brokers, banks, including Japan's largest in MUFG, and several hedge funds, including Millennium Management, Soros Fund, and ExodusPoint. The startup was highlighted as one of Business Insider's up-and-coming fintechs in 2023.

It has a valuation between $115 million and $150 million, Szilagyi said.

How Reflexivity works

The upstart's platform lets stock-picking investors analyze data that covers about 40,000 securities from a dozen different providers, including Refinitiv and the London Stock Exchange Group, the Federal Reserve, and S&P Global. It is also built to alert customers, mostly discretionary investors who work at hedge funds and asset managers, to market events and their potential ripple effects on a given portfolio.

If there's a big move in treasury yields, Reflexivity will automatically examine the ripple effects and see how that could impact banking stocks. In this hypothetical example, Reflexivity would see that its user, say a hedge fund trader, has Wells Fargo stock in her portfolio, and flag to her that Wells Fargo stock historically reacts very well to a rise in yields.

Behind the scenes, a proprietary knowledge graph and generative AI-powered user interface helps users connect the dots and better understand investing relationships, Szilagyi said.

Szilyagyi says he also has an answer to a question many Wall Street technologists are facing with hallucinations, or generative AI's tendency to make up answers that are presented as fact.

Reflexivity's answer is a so-called closed system, wherein the AI models can only pull answers from data that's been pre-vetted by the startup. The reason other models, like OpenAI's ChatGPT, hallucinate is because it operates on an open system that takes in data from anywhere on the internet, Szilagyi said. If it can't find anything, it'll be inclined to make up an answer because these tools are built to deliver some kind of answer, he said.

On top of that, Reflexivity also programmed its models to not force an answer to every question. About 5% of the time, Reflexivity will say it doesn't have the ability to answer a given question if it's unable to generate an answer from the data it's been given, Szilagyi said.

"For finance professionals, the ability to get the candid and honest answer is absolutely critical because it only takes one, two hallucinations to be extremely costly when it comes to trading," Szilagyi said.

Here's Reflexivity's pitch deck it used to raise its Series B.

(Because the startup only recently changed its name, these slides include its former name, Toggle AI.)