Tech
As demand for lithium explodes, battery recycling startup Tozero sprints to scale with $11.7M seed
Tozero, a Munich-based startup that recovers valuable raw materials from recycled lithium-ion batteries, is gearing up to scale. The startup just closed an oversubscribed €11 million seed round (around $11.7M) to step up production by building its first industrial deployment (A.K.A first-of-a-kind or FOAK) plant.
Currently, Tozero’s pilot plant processes nine tonnes of lithium-ion battery waste per day, but the startup is shooting for unlimited capacity in what it hopes will be just another couple of years of scaling its business.
“Other competitors raise way more money to get to industrial plant. But as our process and our technology is so lean and efficient we don’t require more to get to our first industrial deployment, or what the investor world would call the ‘first of a kind’ plant. That’s what we’re aiming to build,” co-founder and CEO Sarah Fleischer (pictured above, left) told TechCrunch.
Once Tozero’s process hits industrial pace and functionality, the startup says there will be no hard limits on what it can achieve in battery recycling as long as it can keep accessing waste streams.
“The purpose of the FOAK is really to enter the proper continuous production — manufacturing — of the product,” co-founder and managing director, Dr. Ksenija Milicevic Neumann, added.
“After that, it’s unlimited, infinite, exponential growth possible,” Fleischer claimed. “Our idea is to operate the plants ourselves worldwide. We focus on Germany, on Europe, and then we go to North America. But after we reach that [FOAK] plant, we can expand Tozero on multiple dimensions around the world. So that’s going to be a key milestone for the next growth phase.”
The startup pointed to projections that global demand for lithium is expected to quadruple to 3.1 million metric tons by 2030, driven by rapid uptake of electric vehicles and growing need for large-scale renewable energy batteries. For context, lithium mining production yielded only 180,000 metric tons last year, so recycling will have a critical role to play in servicing that demand.
The EU’s Battery Directive will also make it mandatory that at least 80% of lithium must be recovered from batteries by 2031.
“The technology works… So the core part of our technology is already nailed. Now we just have to industrialize it,” Fleischer said.
Smashing recycling bottlenecks
The startup is tackling bottlenecks in lithium battery recycling using a water-based carbonation recovery process that’s more environmentally friendly than conventional pyrometallurgy (smelting). Its method of reclaiming lithium also doesn’t entail the use of harsh acids, as can be the case with other battery recycling processes.
Tozero says its method also results in substantially lower emissions — 70% lower — than mining.
“The security of the raw material — it’s national security in a way,” Fleischer said. “There are so many underserved industries here in Europe that are starving for the material because Europe doesn’t produce lithium carbonate; we’re importing. If you look at [European Commission president] Ursula von der Leyen, she makes statements that we import over 97% of the lithium carbonate from China. So we’re highly dependent on the eastern front and mining industries.”
Access to black mass, the byproduct of mechanical recycling of lithium batteries that Tozero processes, is not restricted across borders. And on the competition front, Fleischer describes this as a “completely blue ocean market,” with battery recycling efforts mostly focused elsewhere. The startup says it can use black mass from any type of lithium-ion batteries so the waste streams can be mixed.
“Lithium will be always inside [the batteries for recycling], but the other elements are changing — with innovations in battery manufacturing — so we don’t care if there is nickel, or if it’s a few percent less or more, for example, cobalt, but lithium is always there,” said Milicevic Neumann.
Tozero also reclaims graphite from the black mass waste streams. The startup says its focus on these two critical raw materials is a “key differentiation” versus other battery recycling players.
The focus on lithium is also why the startup has customers beating a path to its door.
“Customers are just storming this place,” Fleischer said, couching market demand as “way too high” for many industrial use-cases in Europe. Tozero has lined up customers worth “over a billion of off-take that are keen to have our material,” she said.
Tozero delivered its first batch of recycled high-purity lithium to commercial customers this April, nine months after opening its pilot facility in Germany.
The need for speed
Tozero was only founded in 2022, so how has it achieved something larger players in the space evidently haven’t managed over the past couple of decades? The startup says it boils down to having a tight focus, being fast and thinking creatively.
Being fast requires being creative when you’re building hardware, Fleischer argued, explaining that the biggest challenge for hardware startups is the issue of delivery times for getting the equipment needed to scale.
“We break things fast, learn, iterate and improve at a very fast pace — probably like Elon Musk’s SpaceX kind of principle — just get stuff building and see [what happens] until things break, learn from it, and iterate and improve in very fast sprints, which is very unfamiliar for hardware companies,” said Fleischer.
“I would say we protect ourselves with speed,” she added, confirming that Tozero’s approach is based on a “process innovation” that’s protected as a trade secret, though it’s not patented. “The entire process, steps or parameters, the order, how we do specific things, that is completely our ‘Coca Cola’ [trade secret] recipe,” she added.
Tozero believes it can expand its approach to reclaim other raw materials that could be used as “energy sources,” though it wouldn’t specify which materials it may add later.
The overarching mission is to get to zero waste of critical raw materials. “We’re quite aware of [the broader challenges entailed in decarbonizing in a sustainable way],” Milicevic Neumann told TechCrunch. “So we want also to focus on recycling of some other materials in the future as well.”
But if it wants to achieve real impact, wouldn’t Tozero have to license its trade secrets to others? The pair say they haven’t fully decided their approach, but prefer to retain control over the process as they scale — though they are open to partnerships.
“On the operational side, we believe we can only really deliver the highest quality if we operate the plants ourselves,” said Fleischer. “This can be also with partners. I mean, we’re open for that. So I don’t want to say ‘yes’ or ‘no’ to licensing. Partnerships are great to scale, if helpful, but we’re going to operate our plants ourselves.”
Tozero’s seed round was led by NordicNinja, with participation from new investors In-Q-Tel (the U.S. strategic public-private fund), Honda, and global infrastructure engineering giant JGC Group. The startup’s €3.5 million pre-seed round, closed around two years ago, was led by Berlin-based Atlantic Labs. To date, Tozero has raised €17 million, which includes a €2.5 million grant from the EU’s R&D support arm, the European Innovation Council.
“Tozero’s innovative approach to battery recycling is exactly what Europe needs to secure key supplies in the global electrification race and Japan would love to collaborate,” said Shin Nikkuni, co-founder and managing partner at NordicNinja, in a statement. “Sarah and Ksenija, two exceptional founders, have the expertise and drive to transform the landscape for sustainable battery solutions. We’re excited to support the tozero team in scaling its technology and commercial operation and contributing to a more sustainable and independent energy future for all.”
This report was updated with a correction to Sarah Fleischer’s title
Tech
Volkswagen’s cheapest EV ever is the first to use Rivian software
Volkswagen’s ultra-cheap EV called the ID EVERY1 — a small four-door hatchback revealed Wednesday — will be the first to roll out with software and architecture from Rivian, according to a source familiar with the new model.
The EV is expected to go into production in 2027 with a starting price of 20,000 euros ($21,500). A second EV called the ID.2all, which will be priced in the 25,000 euro price category, will be available in 2026. Both vehicles are part of the automaker’s new of category electric urban front-wheel drive cars that are being developing under the so-called “Brand Group Core” that makes up the volume brands in the VW Group. And both vehicles are for the European market.
The EVERY1 will be the first to ship with Rivian’s vehicle architecture and software as part of a $5.8 billion joint venture struck last year between the German automaker and U.S. EV maker. The ID.2all is based on the E3 1.1 architecture and software developed by VW’s software unit Cariad.
VW didn’t name Rivian in its reveal Wednesday, although there were numerous nods to next-generation software. Kai Grünitz, member of the Volkswagen Brand Board of Management responsible for Technical Development, noted it would be the first model in the entire VW Group to use a “fundamentally new, particularly powerful software architecture.”
“This means the future entry-level Volkswagen can be equipped with new functions throughout its entire life cycle,” he said. “Even after purchase of a new car, the small Volkswagen can still be individually adapted to customer needs.”
Sources who didn’t want to be named because they were not authorized to speak publicly, confirmed to TechCrunch that Rivian’s software will be in the ID EVERY1 EV. TechCrunch has reached out to Rivian and VW and will update the article if the companies respond.
The new joint venture provides Rivian with a needed influx of cash and the opportunity to diversify its business. Meanwhile, VW Group gains a next-generation electrical architecture and software for EVs that will help it better compete. Both companies have said that the joint venture, called Rivian and Volkswagen Group Technologies, will reduce development costs and help scale new technologies more quickly.
The joint venture is a 50-50 partnership with co-CEOs. Rivian’s head of software, Wassym Bensaid, and Volkswagen Group’s chief technical engineer, Carsten Helbing, will lead the joint venture. The team will be based initially in Palo Alto, California. Three other sites are in development in North America and Europe, the companies have previously said.
“The ID. EVERY1 represents the last piece of the puzzle on our way to the widest model selection in the volume segment,” Thomas Schäfer, CEO of the Volkswagen Passenger Cars brand and Head of the Brand Group Core, said in a statement. “We will then offer every customer the right car with the right drive system–including affordable all-electric entry-level mobility. Our goal is to be the world’s technologically leading high-volume manufacturer by 2030. And as a brand for everyone–just as you would expect from Volkswagen.”
The Volkswagen ID EVERY1 is just a concept for now — and with only a few details attached to the unveiling. The concept vehicle reaches a top speed of 130 km/h (80 miles per hour) and is powered by a newly developed electric drive motor with 70 kW, according to Volkswagen. The German automaker said the range on the EVERY1 will be at least 250 kilometers (150 miles). The vehicle is small but larger than VW’s former UP! vehicle. The company said it will have enough space for four people and a luggage compartment volume of 305 liters.
Tech
The hottest AI models, what they do, and how to use them
AI models are being cranked out at a dizzying pace, by everyone from Big Tech companies like Google to startups like OpenAI and Anthropic. Keeping track of the latest ones can be overwhelming.
Adding to the confusion is that AI models are often promoted based on industry benchmarks. But these technical metrics often reveal little about how real people and companies actually use them.
To cut through the noise, TechCrunch has compiled an overview of the most advanced AI models released since 2024, with details on how to use them and what they’re best for. We’ll keep this list updated with the latest launches, too.
There are literally over a million AI models out there: Hugging Face, for example, hosts over 1.4 million. So this list might miss some models that perform better, in one way or another.
AI models released in 2025
Cohere’s Aya Vision
Cohere released a multimodal model called Aya Vision that it claims is best in class at doing things like captioning images and answering questions about photos. It also excels in languages other than English, unlike other models, Cohere claims. It is available for free on WhatsApp.
OpenAI’s GPT 4.5 ‘Orion’
OpenAI calls Orion their largest model to date, touting its strong “world knowledge” and “emotional intelligence.” However, it underperforms on certain benchmarks compared to newer reasoning models. Orion is available to subscribers of OpenAI’s $200 a month plan.
Claude Sonnet 3.7
Anthropic says this is the industry’s first ‘hybrid’ reasoning model, because it can both fire off quick answers and really think things through when needed. It also gives users control over how long the model can think for, per Anthropic. Sonnet 3.7 is available to all Claude users, but heavier users will need a $20 a month Pro plan.
xAI’s Grok 3
Grok 3 is the latest flagship model from Elon Musk-founded startup xAI. It’s claimed to outperform other leading models on math, science, and coding. The model requires X Premium (which is $50 a month.) After one study found Grok 2 leaned left, Musk pledged to shift Grok more “politically neutral” but it’s not yet clear if that’s been achieved.
OpenAI o3-mini
This is OpenAI’s latest reasoning model and is optimized for STEM-related tasks like coding, math, and science. It’s not OpenAI’s most powerful model but because it’s smaller, the company says it’s significantly lower cost. It is available for free but requires a subscription for heavy users.
OpenAI Deep Research
OpenAI’s Deep Research is designed for doing in-depth research on a topic with clear citations. This service is only available with ChatGPT’s $200 per month Pro subscription. OpenAI recommends it for everything from science to shopping research, but beware that hallucinations remain a problem for AI.
Mistral Le Chat
Mistral has launched app versions of Le Chat, a multimodal AI personal assistant. Mistral claims Le Chat responds faster than any other chatbot. It also has a paid version with up-to-date journalism from the AFP. Tests from Le Monde found Le Chat’s performance impressive, although it made more errors than ChatGPT.
OpenAI Operator
OpenAI’s Operator is meant to be a personal intern that can do things independently, like help you buy groceries. It requires a $200 a month ChatGPT Pro subscription. AI agents hold a lot of promise, but they’re still experimental: a Washington Post reviewer says Operator decided on its own to order a dozen eggs for $31, paid with the reviewer’s credit card.
Google Gemini 2.0 Pro Experimental
Google Gemini’s much-awaited flagship model says it excels at coding and understanding general knowledge. It also has a super-long context window of 2 million tokens, helping users who need to quickly process massive chunks of text. The service requires (at minimum) a Google One AI Premium subscription of $19.99 a month.
AI models released in 2024
DeepSeek R1
This Chinese AI model took Silicon Valley by storm. DeepSeek’s R1 performs well on coding and math, while its open source nature means anyone can run it locally. Plus, it’s free. However, R1 integrates Chinese government censorship and faces rising bans for potentially sending user data back to China.
Gemini Deep Research
Deep Research summarizes Google’s search results in a simple and well-cited document. The service is helpful for students and anyone else who needs a quick research summary. However, its quality isn’t nearly as good as an actual peer-reviewed paper. Deep Research requires a $19.99 Google One AI Premium subscription.
Meta Llama 3.3 70B
This is the newest and most advanced version of Meta’s open source Llama AI models. Meta has touted this version as its cheapest and most efficient yet, especially for math, general knowledge, and instruction following. It is free and open source.
OpenAI Sora
Sora is a model that creates realistic videos based on text. While it can generate entire scenes rather than just clips, OpenAI admits that it often generates “unrealistic physics.” It’s currently only available on paid versions of ChatGPT, starting with Plus, which is $20 a month.
Alibaba Qwen QwQ-32B-Preview
This model is one of the few to rival OpenAI’s o1 on certain industry benchmarks, excelling in math and coding. Ironically for a “reasoning model,” it has “room for improvement in common sense reasoning,” Alibaba says. It also incorporates Chinese government censorship, TechCrunch testing shows. It’s free and open source.
Anthropic’s Computer Use
Claude’s Computer Use is meant to take control of your computer to complete tasks like coding or booking a plane ticket, making it a predecessor of OpenAI’s Operator. Computer use, however, remains in beta. Pricing is via API: $0.80 per million tokens of input and $4 per million tokens of output.
x.AI’s Grok 2
Elon Musk’s AI company, x.AI, has launched an enhanced version of its flagship Grok 2 chatbot it claims is “three times faster.” Free users are limited to 10 questions every two hours on Grok, while subscribers to X’s Premium and Premium+ plans enjoy higher usage limits. x.AI also launched an image generator, Aurora, that produces highly photorealistic images, including some graphic or violent content.
OpenAI o1
OpenAI’s o1 family is meant to produce better answers by “thinking” through responses through a hidden reasoning feature. The model excels at coding, math, and safety, OpenAI claims, but has issues deceiving humans, too. Using o1 requires subscribing to ChatGPT Plus, which is $20 a month.
Anthropic’s Claude Sonnet 3.5
Claude Sonnet 3.5 is a model Anthropic claims as being best in class. It’s become known for its coding capabilities and is considered a tech insider’s chatbot of choice. The model can be accessed for free on Claude although heavy users will need a $20 monthly Pro subscription. While it can understand images, it can’t generate them.
OpenAI GPT 4o-mini
OpenAI has touted GPT 4o-mini as its most affordable and fastest model yet thanks to its small size. It’s meant to enable a broad range of tasks like powering customer service chatbots. The model is available on ChatGPT’s free tier. It’s better suited for high-volume simple tasks compared to more complex ones.
Cohere Command R+
Cohere’s Command R+ model excels at complex Retrieval-Augmented Generation (or RAG) applications for enterprises. That means it can find and cite specific pieces of information really well. (The inventor of RAG actually works at Cohere.) Still, RAG doesn’t fully solve AI’s hallucination problem.
Tech
Not all cancer patients need chemo. Ataraxis AI raised $20M to fix that.
Artificial intelligence is a big trend in cancer care, and it’s mostly focused detecting cancer at the earliest possible stage. That makes a lot of sense, given that cancer is less deadly the earlier it’s detected.
But fewer are asking another fundamental question: if someone does have cancer, is an aggressive treatment like chemotherapy necessary? That’s the problem Ataraxis AI is trying to solve.
The New York-based startup is focused on using AI to accurately predict not only if a patient has cancer, but also what their cancer outcome looks like in 5 to 10 years. If there’s only a small chance of the cancer coming back, chemo can be avoided altogether – saving a lot of money, while avoiding the treatment’s notorious side effects.
Ataraxis AI now plans to launch their first commercial test, for breast cancer, to U.S. oncologists in the coming months, its co-founder Jan Witowski tells TechCrunch. To bolster the launch and expand into other types of cancer, the startup has raised a $20.4 million Series A, it told TechCrunch exclusively.
The round was led by AIX Ventures with participation from Thiel Bio, Founders Fund, Floating Point, Bertelsmann, and existing investors Giant Ventures and Obvious Ventures. Ataraxis emerged from stealth last year with a $4 million seed round.
Ataraxis was co-founded by Witowski and Krzysztof Geras, an assistant professor at NYU’s medical school who focuses on AI.
Ataraxis’ tech is powered by an AI model that extracts information from high-resolution images of cancer cells. The model is trained on hundreds of millions of real images from thousands of patients, Witowski said. A recent study showed Ataraxis’ tech was 30% more accurate than the current standard of care for breast cancer, per Ataraxis.
Long term, Ataraxis has big ambitions. It wants its tests to impact at least half of new cancer cases by 2030. It also views itself as a frontier AI company that builds its own models, touting Meta’s chief AI scientist Yann LeCun as an AI advisor.
“I think at Ataraxis we are trying to build what is essentially an AI frontier lab, but for healthcare applications,” Witowski said. “Because so many of those problems require a very novel technology.”
The AI boom has led to a rush of fundraises for cancer care startups. Valar Labs raised $22 million to help patients figure out their treatment plan in May 2024, for example. There’s also a bevvy of AI-powered drug discovery firms in the cancer space, like Manas AI which raised $24.6 million in January 2025 and was co-founded by Reid Hoffman, the LinkedIn co-founder.
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