To prop up the AI Bubble or not? That is the question. It’s Masa’s money. 💵 💵💵
Skip past the editorial to see the list of the top 145 private AI companies and their current valuations. We are looking forward to your recommendations.
Will SoftBank’s Masayoshi Son invest in the AI Bubble (or not)?
Our speculation over our last two Raps that the private AI company marketplace would inevitably take the DeepSeek trickle-down valuation hit is about to meet a dramatic test. At center stage is, by far, the most highly valued private AI company, OpenAI, which was last valued at $157 billion during its $6.6 billion raise last October.
If we were Masa, we would throw our money in with Elon and his AI company, xAI, which is pursuing a hostile takeover of OpenAI at the moment for a discounted $97.4 billion valuation. (Which we think is still too high but better than $300B😳) If Masa is ready to go, he would be joining Elon and an illustrious group of investors, including Palantir co-founder Joe Lonsdale, Hollywood’s top power broker, Ari Emanuel, CEO of Endeavor (Princess Meghan Merkle’s agent), as well as Valor Equity Partners, Baron Capital, Atreides Management, and Vy Capital.
Elon bought the old Twitter in 2022 for $44 billion and responded to Sam’s X post by calling him a ‘swindler.’
All this complicates Sam's fundraising plans and efforts to convert OpenAI to a for-profit company, which Elon (joined by Zuck and Meta) is already fighting over in court. Since the hostile takeover announcement, Elon has said he would withdraw his bid if OpenAI's board stops its conversion to a for-profit company and preserves its charity's mission. But we all know that Elon knows Sam will never go for that.
‘[Sam Altman and OpenAI] are involved in repeated self-dealing, putting profits over safety, transferring its technology and keeping it closed source, and concentrating AI’s power in the hands of Microsoft. It’s time for OpenAI to return to the open-source, safety-focused force for good it once was. We will make sure that happens.’
—Elon Musk in a court filing last week.
The TechBro shuffle makes for good theatre, but it all comes back to valuation. OpenAI is not going to agree to any offer unless forced by someone like Masa, and that is why he is holding one of the biggest cards at this moment. If Elon's group were to acquire OpenAI, the company would be merged into xAI, which was valued at $50 billion in a $12 billion funding in November. Does Masa, or any other big investor, want to give OpenAI, with all its troubles, $25+ billion at a $300 billion valuation or an Elon-led OpenAI+xAI combo at less than half the price?🤔 We know where we would throw our chips if we were Masa.
A battle of the AI titans. Sam and Elon co-founded OpenAI in 2015 as a charity. Photo generated by xAI.
OpenAI vs. xAI
xAI reached the $50 billion valuation milestone over 8 years faster than OpenAI. xAI also recently released its mobile chatbot app called Grok, which directly challenges OpenAI's ChatGPT. Grok was developed within a year of the company's founding in 2023. By most all measures, xAI is the leaner-meaner, faster-to-market of the two competitors, with the exclusive advantage of accessing X content. Not to mention Elon has THE front row seat to the reinvention of government, where AI will play a central role in its transformation.💰💰💰
We did a back-of-the-envelope AI valuation-to-revenue calculation last week to support our ‘Overvalued AI companies’ post, only to find that—not surprisingly—the venerable Sequoia Capital was nine months ahead of us. Last June, Sequoia Partner David Cahn wrote a post in which he calculated that AI companies need to generate approximately $600 billion in annual revenues to justify the massive investments being made in AI infrastructure.
David Cahn’s simple math
Mr. Cahn says to calculate this metric, take Nvidia’s run-rate revenue forecast and multiply it by 2x to reflect the total cost of AI data centers (GPUs are half of the total cost of ownership—the other half includes energy, buildings, backup generators, etc.). Then you multiply by 2x again to reflect a 50% gross margin for the end-user of the GPU (e.g., the startup or business buying AI compute from Azure or AWS or GCP, who needs to make money as well).
Mr. Cahn’s bottom line was that even if optimistic projections for major tech companies' AI revenues are achieved, that will still leave a $500 billion sales shortfall.😳 This post was a follow-up to his post-AI’s $200B Question- from less than a year earlier. Read Mr. Cahn’s full post here.
Sequoia is an investor in Elon’s xAI, including in the $6 billion Series C funding round in December 2024. The VC powerhouse is reportedly in talks to join a potential new $10 billion funding round that could value xAI at $75 billion—we shall see if the $75B valuation holds up in the coming shakedown.
$200 trillion and counting
We are long-term bullish on the Web3 era and mathematically see it as a 10x Web2 opportunity (that was a $20 trillion boom). Our starting proof point is the 145 first-generation private AI companies introduced below. Yes, some of these companies are gearing up for winner-take-90% of the market, head-on collisions (e.g., OpenAI vs. xAI), with the accompanying startup wreckage that will scatter the Streets of Silicon Valley. However, our AI company list also represents 24 target AI markets, touching almost every major industry—an impressive first sketch of the new, more efficient, self-empowered, and decentralized world we will live in.
We would further note that all great innovations are built upon financial manias, where the average investment dollar loses money in the first round. The golden lining is that the overfunding of Silicon Valley companies accelerates the development of innovation opportunities and keeps the US in front of its global competition.
There are a lot of good things going on. Let’s get back to reality, lower private company valuations, tighten our belts, and strap in for our most disruptive ride yet.
Not a good look boyz.🙄
Lions and tigers and Elon, oh my!
We did include a ‘TechBro backlash’ as one of our top dozen predictions for ‘25. Still, we never calculated that TDS would morph into full-blown EDS.😳 Perhaps we should not be surprised as Elon plays a leading role as a dark or at least ‘directed’ character in the hallucinations of conspiracy theorists from all sides of the spectrum. The Cowardly Lion from the land of DOGE still has them (and Corporate Media) shivering—at least for now.
“The New York Times had a front page story about the horrible ‘Constitutional crisis’ going on. I have been studying the US Constitution for close to 70 years now, and I can tell you there is no Constitutional crisis. The US has a system of checks and balances that has endured for over 230 years. The Democrats and media are crying wolf. People are saying its time to hit the streets—that it is time to declare War! No. No. No. The system is working. We have three independent branches of government, and the bureaucracy is not one of them. Trump is saying its time to look hard at these agencies and the trillions they spend in ways that are not necessarily in the interest of US citizens. That is a good thing. If he pushes the boundaries, the courts will step in, as they did with Biden many times.”
—Alan Dershowitz, Life-long Democrat and former Harvard Law School professor renowned for his expertise in U.S. constitutional law.
Back to reality, Elon imagined and is now running the Department of Government Efficiency (DOGE), a temporary advisory body within the Executive Office of the President. DOGE focuses on reducing federal spending and streamlining government operations, with a set expiration date of July 4, 2026. This is a research and advisory role to the Boogeyman or whomever he designates only, with no authority to order spending cuts, close agencies and programs, fire employees, etc. Any access to government information systems is to read-only, with no ability to tamper.
DOGE consists of 20 folks based in DC who report to Steve Davis, a longtime Musk confidant, and CEO of The Boring Company. Most DOGE associates have worked for Elon's companies like SpaceX and Tesla, and they are embedded at federal agencies to review critical systems, looking for potential waste and fraud. DOGE employees have merely READ-ONLY access to any government database that has been approved for analysis. DOGE claims to have saved taxpayers $37.69 billion since starting its work.
Celebrity Worship Syndrome (CWS)
CWS is an obsessive-addictive disorder where individuals become excessively preoccupied with a public figure, often engaging in compulsive behaviors like constantly seeking information about them and fixating on negative details to degrade them in conversations.
This behavior can interfere with daily life and relationships. CWS is considered a form of parasocial relationship. Extreme cases, categorized as “Borderline-Pathological,” may involve obsessive monitoring, antisocial tendencies, and impulsivity.
Our strong view is that our federal government is now on the road to cutting over 75 percent of its overhead under a new, AI-powered, blockchain-based structure that is much more transparent, decentralized, efficient and requires fewer rules and regulations. This system will also be much better at protecting citizens’ privacy and managing their rights and access to government services. The net result will be much happier citizens, much lower taxes, near-zero inflation, and budget surpluses! 😎🤙🏼
You mean Elon is the real dictator behind the dictator?🤔 This $115,000 ad campaign produced by the usual suspects was nixed by the Washington Post.😳
Silicon Valley U @ DC
Updating the federal government from a 1980s bureaucracy to a more modern, flatter, innovation-savvy operation will happen. But it also means the elimination of hundreds of thousands of government employees jobs.—Seveventy-seven thousand federal workers (3%) have already opted for the ‘deferred resignation’ offer. The Cowardly Lion, et al can be blamed for not showing some empathy—as these are real people with real families— and we should invest in them during their transition to the private market.
‘If I only knew how AI coud make me more productive at what I love!’💡
We propose creating a ‘pop-up’ university—Silicon Valley U @ DC—that draws upon ‘guest lecturers’ from Silicon Valley’s top companies, to expose public employees to the emerging worild of AI, blockchain, crypto, robotics, autonomous vehicles and drones, virtual reality, greentech and other cutting edge innovations and how they are being applied across industries. This training program would be a great investment, it is the right and fair thing to do, and comes with a huge secondary benefit of keeping our government closer to the innovation edge. Importantly it can also soften fears, and inspire more optimism around positive change.
“We can't sustain a system that bleeds billions of taxpayer dollars on programs that have outlived their usefulness or exist solely because of the power of politicians, lobbyists or interest groups. We are going to go through our federal budget as I promised during the campaign, page by page, line by line eliminating those programs we don't need and insisting that those that we do need operate in a sensible, cost effective way.”
—President Barak Obama on February 24, 2009, during his Address to Joint Session of Congress. President Obama went on to sign off on $5 trillion worth of new legislative costs and drove the federal debt up an additional $4.6 trillion.
Every President started their administration with the intention of downsizing the scope and power of government. Obama wanted to do it, and the Boogeyman, with the help of the Cowardly Lion, will make it happen. It’s not a power grab because, by definition, its purpose is to decentralize power away from the executive and legislative branches and the US federal government in general and back to the people. It also means more privacy and empowerment of the individual.
Who in the modern world is against this?
The downsizing of the US government will happen because the Bogeyman has the power to do it, and there is no putting the Cowardly Lion back in his cage. It will also happen because cutting government waste and fraud is what US citizens want, and in a free market society, customers generally end up getting what they want. The TechBro’s should lead the charge on investing into the re-training of existing and furloughed government employees to help them become more Web3-savvy. These efforts will also help ease the TechBro backlash—if that is even possible.
We know the DOGE Squad looks young and goofy, but they are very committed and very smart. We need to take a deep breath, let the children play, and trust there will be adults (the courts) in the room to make sure they don’t misbehave.
As the TechBro backlash escalates, Zuck’s living his best life!
As it is in the land of DOGE, it is in the land of BigTech
As we also predicted for 2025, the slashing, burning, and retrofitting proposed by the DOGE team is now being emulated in Big Tech. Zuck recently announced cutting 3,600 (5% of its workforce) of Meta's 'lowest performers.'
There are two major themes in BigTech's downsizing. First, the 'managerial class structure' is being replaced by flatter organizations driven by a new, AI-empowered worker class tied to specific output and results. Second, there is a shift to investing in AI development, as every tech company must become an AI company in its own right to survive and thrive in Web3.
A asl Cryptonite Weekly Rap’s paid members gain access to company and investor lists and analytics and enjoy invitations to private events and global summits. 💪🏼😎
Introducing the top private AI companies for 2025! —Who are we missing?
We are pleased to present our current list of top private AI companies. The final list will be included on our Cryptonite 300 Top Companylist for 2025, which will also feature blockchain, crypto, robotics, autonomous vehicles, and other top Web3 companies. The final Cryptonite 300 list will be released by March 15th.
Picking these companies is not a perfect science, in part because they are still private and, by nature, only disclose so much. In that spirit, we want to present an early look at this list to our readers so we can still get a heads up on companies we might be missing. We are also interested to learn about companies on our list that may be sputtering and need a second look. We acknowledge that however we land, there will be great companies we will miss. But as we tell disappointed entrepreneurs—There is always next year’s list!
Please email us with any confidential input and company recommendations to TheEditor@cryptoniteventures.com 😎🙏🏼
The most challenging data to collect is a company's valuation, which we include as a best guess from a variety of sources for each company below. But keep in mind that these numbers are very dynamic and can change with new funding or if the AI market corrects, as we are betting will happen. Speaking of valuations, our standard criteria for making our top lists is ROI potential. As our readers know, we have been blowing the AI Bubble whistle for over a year now, so we need to suspend that criterion for the time being. (In other words, now is not the time to buy.😉)
The one thing we can guarantee is that this is a great list of first-generation AI companies. If our track record continues, at least 50 percent of the companies will have some form of a 'successful exit.' We also encourage readers to imagine how any of these companies affect the industries you are operating in and how you might leverage these top companies to develop new expertise and create new opportunities for success.
We look forward to hearing from anyone with a hot company tip and appreciate any feedback as always. TheEditor@cryptoniteventures.com
Artificial Intelligence Top Companies
Click on the top company link and…
…get a Perplexity.ai Pro search result that will offer a real-time profile of each top AI company, including team member backgrounds, product and service descriptions and competitive advantage, VC funding track record and investors, and links to primary sources. Our editors also usedxAI's new Grok2 mobile search for additional cross-referencing, which we also recommend.
AI Large Language Model (LLM) Providers
01.AI, Beijing, China, Founded in 2023 — ($1.2 billion)
Develops large language models (LLMs) and AI applications. Their first product is Yi-34B, an open-source neural network with 34 billion parameters that can process text in English and Chinese. Target buyers include tech companies and researchers needing scalable AI solutions.
Anthropic, San Francisco, CA, USA, Founded in 2021 — ($60 billion)
Developed Claude, a conversational AI model focused on leveraging natural language that prioritizes safety, ethical considerations, and reliability. Target buyers include enterprises needing trustworthy AI for complex decision-making.
Cohere, Toronto, Canada, Founded in 2019 — ($5.5 billion)
An API that provides access to large language models and natural language processing tools for enterprise AI applications. . Target buyers include software developers and enterprises looking to integrate AI into applications. Target buyers include software developers and enterprises looking to integrate AI into applications.
Krutrim, Bengaluru, India, Founded in 2023 — (1 billion)
India’s first complete AI computing stack, including large language models and AI infrastructure tailored for Indian languages and cultural contexts. Target buyers are Indian consumers, developers, enterprises, and researchers.
Mistral AI, Paris, France, Founded in 2023 — ($6.2 billion)
Develops open-source, open-weight large language models (LLMs) focused on natural language processing. Target buyers include tech companies and developers needing flexible AI tools.
OpenAI, San Francisco, CA, USA, Founded in 2015 — ($157 billion)
Pioneers in general-purpose AI, primarily known for models like GPT for text generation, and also a provider of versatile AI solutions for enterprises. Target buyers include developers and enterprises across multiple sectors.
Sakana AI, Tokyo, Japan, Founded in 2023 — ($1 billion)
Developing nature-inspired AI foundation models, leveraging principles such as evolution and collective intelligence to create resource-efficient AI technologies that can generate text, images, video, and code. Target buyers include enterprises in Japan and globally seeking advanced, adaptable AI solutions tailored to specific industry challenges.
xAI, San Francisco, CA, USA, Founded in 2023 — ($50 billion)
General-purpose AI is currently known for its Grok2 text generation service and plans to become an AI solution for enterprises. Target buyers include consumers and enterprises across multiple sectors and industries.
AI Platforms
Aleph Alpha, Heidelberg, German, Founded in 2019 — ($489 million)
Develops sovereign AI technology with a focus on transparency, explainability, and compliance with European data protection regulations. Target buyers include European enterprises and government agencies looking for secure, compliant AI solutions that prioritize data sovereignty.
Baseten, San Francisco, CA, USA, Founded in 2019 — ($200 million)
Enables developers to deploy machine learning models as scalable APIs, simplifying the process of model deployment and management. Target buyers include software developers and data scientists in tech companies who need to integrate AI models into their applications.
Clarifai, New York, NY, USA, Founded in 2019 — ($775 million)
Offers a comprehensive AI platform for developers to build, deploy, and scale visual recognition applications with pre-trained models. Target buyers include businesses in sectors like retail, healthcare, and media for visual AI solutions.
Hugging Face, Brooklyn, NY, USA, Founded in 2016 — ($4.5 billion)
Known for its platform that hosts and shares machine learning models, facilitating AI model collaboration and deployment. Target buyers include developers, researchers, and companies in the AI ecosystem.
Together AI, San Francisco, CA, USA, Founded in 2022 — ($1.3 billion)
Provides infrastructure for AI model development, allowing for collaborative and scalable AI research. Target buyers include AI startups, researchers, and large tech companies.
Weights & Biases, San Francisco, CA, USA, Founded in 2017 — ($1.3 billion)
Offers tools for machine learning experiment tracking, dataset versioning, and model management, enhancing reproducibility and collaboration. Target buyers include data scientists and ML engineers in tech-driven organizations.
AI Search
DeepSeek, Hangzhou, Zhejiang, China, Founded in 2023 — (Undisclosed)
An open source platform that focuses on AI-driven search technology that deeply understands user intent, enhancing search relevance. Target buyers include companies looking for advanced search solutions to improve user engagement.
Aravind Srinivas, Cofounder and CEO of Perplexity.
Perplexity, San Francisco, USA, Founded 2022 — ($9 billion)
Offers an AI-powered answer engine for complex queries, delivering precise information synthesis. Target buyers include consumers, professionals, and businesses needing detailed, research-based answers.
Agriculture & Food
Afresh, Oakland, CA, USA, Founded 2017 — ($410 million)
Leverages AI to optimize the fresh food supply chain by providing accurate demand forecasting and inventory management, reducing food waste, and increasing profitability with their Fresh Operating System. Target buyers include grocery retailers, and supermarkets focused on managing perishable goods.
Taranis, Sao Paulo, Brazil & Tel Aviv-Yafo, Israel, Founded 2022 — ($500 million)
Employs AI-driven precision agriculture technology, using computer vision and deep learning to analyze high-resolution aerial imagery for crop health monitoring, and enable early detection of pests and diseases to enhance yield. Target buyers include agribusinesses, agricultural advisors, and large-scale farmers interested in precision farming solutions.
Business Intelligence
Acceldata, Campbell, CA, USA, Founded in 2018 — ($360 million)
Provides an AI-driven data observability platform that ensures data quality, pipeline health, and infrastructure efficiency, giving organizations actionable insights for data management. Target buyers include data executives and engineers in enterprises needing robust data management solutions.
Alation, Redwood City, CA, USA, Founded 2012 — ($1.8 billion)
Provides data discovery, governance, and analytics, facilitating more straightforward access to trusted data for better decision-making. Target buyers include data analysts, data stewards, and business intelligence teams in companies aiming to enhance data literacy and governance.
Altana AI, New York, NY, USA, Founded 2018 — ($1 billion)
An AI-driven platform that maps and analyzes global supply chains for enhanced visibility and risk management. Target buyers include governments, major logistics providers, and large enterprises seeking to improve supply chain transparency, compliance, and sustainability.
Bigeye, San Francisco, CA, USA, Founded in 2019 — ($400 million)
Provides data observability solutions powered by AI to detect anomalies and ensure data quality in real-time. Target buyers include tech companies' data engineers and analysts.
DevRev, Palo Alto, CA, Founded 2020 — ($1.2 billion)
An AI-native platform that unifies customer support, product development, and enterprise functions using knowledge graphs and large language models. Target buyers include SaaS companies and enterprises seeking to enhance collaboration, increase product velocity, and reduce customer churn through AI-driven solutions.
FourKites, Chicago, IL, USA, Founded in 2014 — ($1 billion)
Provides an AI-driven Intelligent Control Tower that integrates real-time visibility, digital twins, and autonomous agents to predict and prevent supply chain disruptions while automating execution. Target buyers include Fortune 2000 shippers, and 3PLs and carriers seeking end-to-end supply chain orchestration.
Glean, Palo Alto, CA, Founded 2019 — ($4.6 billion)
A generative AI platform that enhances enterprise search and automates workflows by connecting and analyzing a company’s internal data and applications. Target buyers include large enterprises across industries like technology, finance, and healthcare.
H20.ai, Mountain View, CA, USA, Founded in 2012 — ($1.7 billion)
Its open-source machine learning platform democratizes AI by allowing users to build predictive models quickly. Target buyers include businesses in finance, insurance, and healthcare looking to implement predictive analytics.
Hebbia, New York, NY, USA, Founded in 2020 — ($700 million)
Uses generative AI to automate document analysis and data extraction from unstructured sources, speeding up information processing. Target buyers include legal professionals, investment firms, and any sector dealing with large volumes of document analysis.
Quantexa, London, UK, Founded in 2016 — ($1.8 billion)
Data-driven decision-making tools that connect data to uncover hidden insights using AI-driven entity resolution and network analytics. Target buyers include financial services, government agencies, and insurance companies.
Scale AI, San Francisco, CA, USA, Founded in 2016 — ($13.8 billion)
Provides high-quality data annotation services powered by human-in-the-loop processes to train AI models effectively. Target buyers include autonomous vehicle companies, tech firms, and any entity requiring large-scale data labeling.
SymphonyAI was founded in 2017 by Dr. Romesh Wadhwani, an Indian-American billionaire entrepreneur who had self-funded his startup, which has become one of the fastest-growing B2B AI companies on the planet.
SymphonyAI, Palo Alto, CA, USA, Founded 2017 — (Undisclosed)
Provides enterprise AI SaaS products that combine predictive and generative AI to deliver insights, transform workflows, and boost productivity Target buyers include retail, finance, and manufacturing sectors. Target buyers include retail, finance, and manufacturing sectors.
Chip Design and Manufacturing
Ayar Labs, San Jose, CA, USA, Founded 2015 — ($1 billion)
Pioneering optical interconnect solutions by integrating light-based communication into silicon chips for faster, more efficient data transfer. Target buyers include companies in high-performance computing, AI, and data centers looking to overcome bandwidth and power constraints in data-intensive applications.
Celestial AI, Santa Clara, CA, USA, Founded 2020 — ($1.2 billion)
Innovates with optical interconnect technology to dramatically increase data transfer rates within data centers, enhancing AI workload performance. Target buyers include data center operators and cloud service providers aiming to optimize data processing speed and energy efficiency.
Cerebras Systems founder & CEO Andrew Feldman with a Wafer-Scale Engine (WSE-2), the revolutionary deep learning central processor.
Cerebras Systems, Sunnyvale, USA, US, Founded 2015 — ($4 billion)
Creates the world's largest single-die AI chip, the Wafer Scale Engine (WSE), for accelerated AI model training at scale. Target buyers include large enterprises, research institutions, and government labs needing massive computational power for AI research and development.
D-Matrix, Santa Clara, CA, USA, Founded 2019 — ($1 billion)
Pioneers in-memory computing for AI with their digital in-memory Compute (DIMC) technology, focusing on energy-efficient AI inference. Target buyers include companies deploying AI at the edge or in data centers looking for performance and power efficiency.
Enfabrica, San Francisco, CA, USA, Founded 2019 — ($1 billion)
Develops scalable network and memory fabrics to optimize data movement for AI workloads, enhancing system scalability and performance. Target buyers include data center architects and AI infrastructure builders requiring high-performance networking solutions.
Etched.ai, San Francisco, CA, USA, Founded 2022 — ($1 billion)
Focuses on custom silicon for AI, particularly accelerators tailored for specific AI models to optimize performance and cost. Target buyers include large tech companies and AI startups needing custom hardware solutions for their AI applications.
Groq, Mountain View, CA, USA, Founded 2016 — ($2.8 billion)
Builds Language Processing Units (LPUs) for extremely fast AI inference, aiming at low-latency AI applications. Target buyers include enterprises and cloud service providers deploying AI inference at scale, particularly in areas like natural language processing.
Neuralink, Fremont, CA, USA, Founded 2016 — ($5 billion)
Develops brain-machine interfaces to merge human cognition with AI, focusing on health applications like treating neurological disorders. Target buyers include medical and research institutions and potential consumers for future consumer-grade enhancements.
Positron, Oakland, CA, USA, Founded 2023 — ($500 million)
Innovates with AI hardware designed for the economics of AI, focusing on performance and cost-effectiveness for AI training and inference. Target buyers include businesses and researchers needing cost-effective AI hardware solutions for various applications.
Rebellions, Seongnam, South Korea, Founded 2020 — ($1.5 billion)
It specializes in AI chips for deep learning, mainly targeting the efficiency and speed of large language models (LLMs). Target buyers include companies in the tech sector, especially those developing or using AI for language processing.
Offers reconfigurable dataflow units (RDUs) that adapt to various AI workloads, providing flexibility and performance for AI models. Target buyers include enterprises needing versatile AI solutions for both training and inference, from cloud to on-premise.
Tenstorrent, Toronto, Canada, Founded 2016 — ($2.6 billion)
Designs high-performance AI chips based on RISC-V architecture for both training and inference, emphasizing open-source and customizability. Target buyers include tech companies, AI developers, and cloud service providers needing flexible, high-performance AI hardware.
Consumer & Prosumer Language & Grammar Tools
DeepL, Cologne,Germany, Founded 2017 — ($2 billion)
Provides superior machine translation services, distinguishing itself with high-quality natural language processing. Target buyers include businesses and individuals needing precise multilingual communication.
Grammarly, San Francisco, USA, Founded 2009 — ($8.1 billion)
Leverages AI for grammar, spelling, and tone detection, offering real-time writing suggestions to enhance communication. Target buyers include professionals, students, and anyone who communicates via written text and is looking to improve clarity and effectiveness in their writing.
Speak, San Francisco, USA, Founded 2016 — ($1 billion)
Offers an AI-powered platform for transcription, translation, and analysis, providing high accuracy and affordability. Target buyers include businesses, researchers, and individuals across various sectors needing efficient, multilingual communication and data analysis tools.
Writer, San Francisco, CA, USA, Founded in 2020 — ($1.9 billion)
Offers AI-driven writing assistance for enterprise content, emphasizing brand consistency and quality. Target buyers include businesses needing to scale content creation while maintaining brand voice.
Content Creation & Production Tools
Bending Spoons, Milan, Italy, Founded 2013 — ($2.6 billion)
Mobile app with AI-driven features in apps like Splice for video editing, leveraging machine learning for intuitive user interfaces. Target buyers include individual consumers, especially creatives and hobbyists in mobile content creation.
Descript founder & CEO Andrew Mason, previously founded Groupon in 2008, one of the fastest-growing companies of all time, reaching a $1 billion valuation in just 16 months.
Descript, Palo Alto, CA, USA, Founded 2017 — ($550 million)
Offers AI-powered audio and video editing where text can be edited as if it were a document, simplifying content creation. Target buyers include content creators in podcasting, video production, and digital media who need efficient editing tools.
ElevenLabs, New York, NY, USA, Founded 2024— ($3.3 billion)
Provides advanced AI voice synthesis technology for creating realistic, multilingual voiceovers with emotional nuances, used in content creation, dubbing, and interactive AI assistants. Target buyers include media production companies, developers of virtual assistants, and businesses in need of voiceover services.
Gamma, San Francisco, CA, USA, Founded 2022 — ($400 million)
Leverages AI to transform traditional presentation creation with features like interactive galleries, dynamic data visualization, and content automation. Target buyers include professionals in marketing, product development, and corporate communications.
Luma AI, Palo Alto, CA, USA, Founded 2021 — ($300 million)
Specializes in AI for vision and graphics, particularly in generating 3D models from 2D images for various applications. Target buyers are in industries such as gaming, VR, and design.
Midjourney, San Francisco, CA, USA, Founded 2022 — ($10 billion)
Creates AI-generated art through user prompts, offering a unique creative tool for digital art. Target buyers include artists, designers, and content creators seeking novel visual content.
Moonvalley, Toronto, Canada, Founded 2023 — ($400 million)
Specializes in AI for music composition, enabling music creation tailored to specific moods or genres. Target buyers include musicians, content creators, and media production companies.
Pika cofounder and CEO Demi Guo grew up in Silicon Valley and started the company with Chenlin Meng (CTO), both former PhD students from Stanford University's AI Labs.
Pika, Palo Alto, CA, USA, Founded 2023 — ($470 million)
Focuses on AI for animation, simplifying the process of creating animated content from static images. Target buyers include animators, game developers, and digital content creators.
Runway, New York, NY, USA, Founded 2017 — ($4 billion)
Innovates in AI for video editing and creation, making complex edits accessible with machine learning. Target customers include filmmakers, content creators, and media companies.
Stability AI, London, United Kingdom, Founded 2024— ($1.3 billion)
Advances in generative AI, particularly for creating stable and diverse images from text descriptions. Target buyers include artists, marketers, and tech companies interested in AI-generated visuals.
Customer Service Automation
AI21 Labs, Tel Aviv, Israel, Founded 2017 — ($1.4 billion)
Known for its Jurassic-1 language model, which provides state-of-the-art natural language understanding and generation, powering its text-based AI services. Target buyers include businesses seeking to enhance customer interaction.
Baichuan, Beijing, China, Founded 2023 — ($2.8 billion)
Develops AI models with a strong emphasis on Chinese language processing, enhancing applications in education and content creation. Target buyers include educational institutions and media companies in China.
EliseAI cofounder & CEO Minna Song has a CS degree from MIT, and previously worked as an AA at a real estate firm in NYC where she observed inefficiencies in the business that AI could solve.
EliseAI, New York, NY, USA, Founded 2017 — ($1.1 billion)
Offers an AI-powered conversational platform that automates property management tasks and resident communications across email, SMS, webchat, and voice, enhancing operational efficiency. Target buyers include property management firms, and healthcare providers seeking to streamline and improve customer interactions.
Cresta, Palo Alto, CA. USA, Founded 2023 — ($1.6 billion)
Offers a generative AI platform that transforms contact center operations with real-time coaching, quality management, and AI-driven insights. Target buyers include large enterprises with contact centers, aiming to enhance agent performance, customer satisfaction, and operational efficiency.
Mercor, San Jose, CA, USA, Founded in 2023 — ($2 billion)
Focuses on AI-driven personalization for e-commerce, improving user experience through tailored recommendations. Target buyers include e-commerce businesses.
Sierra founder Bret Taylor is the former Co-CEO of Salesforce andCTO at Facebook, and is currently chairman of the board at OpenAI.
Sierra, Austin, TX, CA, USA, Founded in 2024 — ($4.5 billion)
It uses AI to help automate customer service with natural language processing for better, more human-like interactions. Target buyers include enterprises in customer service-intensive sectors like telecommunications and retail.
Stepfun, Shanghai, China, Founded 2023 — ($1 billion+)
Develops AI models for conversational interfaces, enhancing customer service bots with more human-like interactions. Target buyers include customer service departments in various industries.
Cybersecurity
Abnormal Security, San Francisco, CA, USA, Founded 2018 — ($5.1 billion)
Utilizes machine learning and AI to understand human behavior to detect and stop email-based cyber threats, including account compromise and phishing. Target buyers include enterprise security teams in large organizations seeking to protect email systems.
Advance.AI, Singapore, Founded 2016 — ($2 billion)
Leverages AI for identity verification and risk management, offering solutions that enhance digital onboarding and fraud prevention. Target buyers include financial institutions, e-commerce platforms, and other businesses requiring robust identity verification.
Cyera, New York, NY, USA, Founded 2021 — ($3 billion)
Cyera uses AI to provide context-aware data security, offering an AI-powered platform that understands data usage and secures it across complex digital environments. Target buyers include security teams at companies, especially those with extensive data operations in tech, finance, and healthcare.
Halcyon, Austin, TX, USA, Founded 2021 — ($1 billion)
Halcyon's innovation lies in its anti-ransomware technology that uses AI for real-time threat detection and prevention, focusing on stopping attacks before data encryption. Target buyers include businesses of all sizes, particularly those in sectors like healthcare, education, and small to medium enterprises vulnerable to ransomware.
Snyk, Boston, MA, USA, Founded in 2015 — ($7.4 billion)
Focuses on security by providing tools to find, fix, and monitor vulnerabilities in open-source dependencies used in software development. Target buyers includes developers and security teams in software companies, especially those using open-source libraries.
Tessl, London, UK, Founded in 2024 — ($750 million)
Provides AI-powered cybersecurity solutions, focusing on threat detection and response, leveraging machine learning to adapt to new threats. Target buyers include companies across various industries that prioritize cybersecurity, particularly in finance and IT.
Molly Gibson is the cofounder and chief innovation officer at Generate Biomedicines, a new Generative Biology platform to develop novel drugs and therapies.
Drug Discovery & Therapeutics
3T Biosciences, San Francisco, CA, USA, Founded 2018 — ($300 million)
Employs an AI platform to predict T-cell receptor specificity, enhancing cancer immunotherapy development. Target buyers include biotech firms, and pharmaceutical companies focused on personalized cancer therapies.
Anagenex, Lexington, MA, USA, Founded 2019 — ($120 million)
A machine learning-driven platform for the directed evolution of small molecules, enabling rapid and extensive testing of compounds to discover new drug candidates for challenging targets. Target buyers include pharmaceutical companies and biotech firms focused on drug discovery.
Atomwise, San Francisco, CA, USA, Founded 2012 — ($500 million)
Uses AI to analyze genetic data to identify biomarkers, which supports its precision medicine offerings. Target buyers include clinical research organizations and healthcare providers aiming for personalized treatment plans.
Leverages AI to understand aging at a molecular level, driving the development of therapeutics for age-related diseases. Target buyers include pharmaceutical companies and investors interested in longevity and age-related disease treatments.
Formation Bio, New York, NY, USA, Founded 2018 — ($1.5 billion)
Integrates AI with human expertise to optimize clinical trial design and data analysis for drug development. Target buyers include pharma companies aiming to streamline clinical trials and drug development processes.
Freenome, South San Francisco, CA, USA, Founded 2014 — ($2.5 billion)
Employs AI to interpret multi-omics data for early cancer detection through liquid biopsies. Target buyers include healthcare providers and patients interested in non-invasive cancer screening.
Uses generative AI to design novel proteins for drug development, bypassing traditional drug discovery bottlenecks. Target buyers include biopharma companies seeking innovative drug development strategies.
Insilico Medicine, Cambridge, MA, USA, Founded 2014 — ($895 million)
Pioneers AI in drug discovery, focusing on aging and age-related diseases using their GENTRL platform. Target buyers include the biotech and pharmaceutical sectors interested in AI-driven drug discovery for aging diseases.
Insitro founder & CEO Daphne Koller was previously cofounded Coursera and was a professor at Stanford University for 18 years.
Insitro, South San Francisco, CA, USA, Founded 2018 — ($2.5 billion)
Applies AI to generate insights from biological data for disease modeling and drug discovery. Target buyers include drug developers needing data-driven biological insights.
Liquid AI, Boston, MA, USA, Founded 2023 — ($2 billion)
Focuses on AI to optimize drug discovery processes, enhance speed, and reduce costs. Its market includes pharmaceutical and biotech companies.
Xaira Therapeutics, South San Francisco, CA, USA, Founded 2024 — ($2.5 billion)
Focuses on AI for discovering therapies by targeting previously inaccessible biological pathways. Target buyers include biotech and pharma companies interested in innovative therapeutic approaches.
Zephyr AI, McLean, VA, USA, Founded 2020 — ($800 million)
Provides AI solutions for predicting patient outcomes, enhancing clinical decision-making in oncology. Target buyers include oncologists, hospitals, and health systems aiming to improve patient treatment strategies.
Finance, Investment & Accounting
9fin, San Francisco, CA, USA, Founded in 2015 — ($400 million)
An AI-powered analytics platform that provides faster, smarter intelligence for debt capital markets by extracting and analyzing key data from bond and loan documentation. Target buyers include investment banks, hedge funds, asset managers, private equity firms, distressed debt advisors, and law firms operating in global credit markets.
AlphaSense, New York, NY, USA, Founded 2014 — ($4 billion)
Leverages AI to provide a market intelligence platform that aggregates and analyzes data from millions of documents for insights in real time. Target buyers include financial institutions, corporations, and consultancies needing in-depth market research.
Anyfin, Stockholm, Sweden, Founded in 2017 — ($400 billion)
Uses AI to analyze photos of receipts and documents to offer instant loans based on financial behavior, providing a streamlined personal loan service. Target buyers include individual consumers looking for quick, hassle-free financial solutions.
Dataiku, New York, NY, USA, Founded 2018 — ($3.7 billion)
Platform democratizes AI with its focus on Everyday AI, allowing businesses to build, deploy, and manage AI models at scale with ease. Target buyers include data scientists, analysts, and business teams across various industries looking to leverage data for decision-making.
DataSnipper CEO Vidya Peters with co-founders Maarten Alblas, Jonas Ruyter and Kai Bakker.
DataSnipper, Amsterdam, Netherlands, founded 2017 — ($1 billion)
An AI-powered intelligent automation platform embedded in Excel, automating repetitive audit and finance tasks to boost efficiency and accuracy. Target buyers include audit and finance professionals, particularly at large accounting firms ,as well as internal audit teams in banking, insurance, and manufacturing sectors.
Datarails, Tel Aviv-Yafo, Israel,Founded 2018 — ($500 million)
Automates financial reporting and planning with AI, integrating with existing systems to streamline financial data analysis. Target buyers include financial professionals and CFOs in mid to large enterprises.
FundGuard, New York, NY, USA, Founded 2018 — ($400 million)
Provides a cloud-native, AI-powered, multi-asset class investment accounting platform. Target buyers include asset managers, asset owners, custodian banks, and fund administrators.
TaxBit, Draper, UT, USA, Founded 2018 — ($1.3 billion)
Uses AI to automate tax calculations and compliance for digital assets, ensuring accuracy and efficiency in handling cryptocurrency taxes. Target buyers include crypto businesses, investors, and accounting firms that need to navigate the complex tax implications of digital currencies.
Healthcare Diagnostics & Administration
Abridge, Pittsburgh, PA, USA, Founded in 2018 — ($2.8 billion)
Uses AI to create medical documentation automatically from doctor-patient conversations, enhancing record accuracy and patient care. Target buyers include healthcare providers, focusing on physicians.
Aidoc, Tel Aviv, Israel, Founded in 2016 — ($800 million)
It focuses on AI for medical imaging, aiding in the rapid detection of life-threatening conditions. Target buyers include radiology departments and hospitals.
AKASA, San Francisco, CA, USA, Founded in 2018 — (1.1 billion)
AI is employed to automate administrative healthcare tasks, like billing and coding, to improve efficiency. Target buyers include healthcare administrative departments and revenue cycle management teams.
Ambience Healthcare, San Francisco, CA, USA, Founded in 2023 — ($350 million)
Automates administrative tasks in healthcare, like note-taking during patient visits, using natural language processing and voice recognition. Target buyers include healthcare providers, including hospitals and clinics, looking to reduce administrative burdens.
Biofourmis, Boston, MA, USA, Founded in 2015 — ($1.3 billion)
Offers AI-powered remote patient monitoring with predictive analytics for personalized care. Target buyers include healthcare providers and patients requiring home care.
Hippocratic AI, Palo Alto, CA, USA, Founded in 2023 — ($1.6 billion)
Develops AI to enhance healthcare interactions, focusing on patient communication and diagnostics through AI-driven virtual health assistants. Target buyers include healthcare providers and medical institutions seeking to improve patient care and efficiency.
A cloud-based, AI-powered platform that simplifies the creation and scaling of digital health solutions, featuring no-code configuration and regulatory-compliant tools for care and research. Target buyers include healthcare providers, pharmaceutical companies, governments, and digital health startups seeking to accelerate digital-first care and clinical research globally.
Rad AI, San Francisco, CA, USA, Founded in 2018 — ($520 million)
Uses AI to automate radiology report writing, enhancing the speed and consistency of diagnostic reporting. Target buyers include radiology practices and hospitals seeking to increase productivity and reduce report turnaround times.
Sword Health, New York, NY, USA, Founded in 2015 — ($3 billion)
Offers an AI-driven digital physical therapy platform that personalizes treatment plans. Target buyers include employers, health insurers, and individuals seeking accessible, effective physical therapy.
Zhipu AI, Beijing, China, Founded in 2019 — ($2.7 billion)
Innovates in AI for healthcare diagnostics and personalized medicine, leveraging big data. Target buyers include the healthcare industry, including hospitals and clinics.
Human Resources
A.Team, New York, NY, USA, Founded in 2019 — ($400 million)
leverages AI to dynamically assemble and manage teams for software development projects, optimizing productivity and project outcomes. Target buyers include tech companies needing flexible, high-performing development teams.
Eightfold AI, Palo Alto, CA. USA, Founded 2016 — ($2.1 billion)
Eightfold innovates with an AI-powered Talent Intelligence Platform that optimizes talent acquisition, management, and workforce planning for enterprises. Target buyers include large enterprises and HR departments across industries like technology, finance, and healthcare.
Sense, San Francisco, CA, USA, Founded 2016 — ($500 million)
An AI-driven talent engagement platform that automates recruiting tasks and personalizes candidate interactions to streamline the hiring process. Target buyers include enterprise recruiting teams and staffing agencies, such as Adecco, Coca-Cola, and Dell.
Infrastructure
Alluxio, San Mateo, CA, USA, Founded in 2015 — ($400 million)
Develops an AI-driven data orchestration layer for big data and AI workloads, improving speed and efficiency. Target buyers include data engineers in cloud and on-premise environments.
Anyscale, San Francisco, CA, USA, Founded in 2019 — ($1.1 billion)
A platform that simplifies scaling distributed applications, particularly machine learning workloads, providing both performance and ease of use. Target buyers include data scientists and engineers at tech companies scaling AI applications.
CoreWeave, Roseland, NJ, USA, Founded in 2017 — ($23 billion)
Delivers cloud infrastructure optimized for GPU-intensive workloads, significantly reducing costs and improving performance for AI and ML tasks. Target buyers include AI researchers, startups, and enterprises requiring high-performance computing resources.
Databrickswas co-founded in 2013 by seven researchers from UC Berkeley's AMPLab: Ali Ghodsi, Matei Zaharia, Ion Stoica, Reynold Xin, Patrick Wendell, Andy Konwinski, and Scott Shenker.
Databricks, San Francisco, CA, USA, Founded in 2013 — ($62 billion)
Offers the Lakehouse platform, which combines data lakes and data warehouses to enable scalable data processing and machine learning, providing a unified analytics platform. Target buyers include large enterprises in industries like finance, healthcare, and retail that need robust data solutions.
Lambda, San Jose, CA, USA, Founded in 2023 — ($1.5 billion)
Offers GPU cloud computing tailored for deep learning, providing the computational power needed for AI model training. Target buyers include AI researchers and developers in need of high-performance computing resources.
Weaviate, Amsterdam, Netherlands, Founded in 2019 — ($500 million)
Provides a vector search engine optimized for machine learning data, allowing for semantic search within databases. Target buyers include developers and companies needing advanced search capabilities for unstructured data like images or text.
Weka, Campbell, CA, USA, Founded in 2013 — ($1.6 billion)
Platform is designed for high-performance computing, especially for AI and ML, by providing ultra-fast storage solutions. Target buyers include enterprises in data science, financial services, media, and any sector with high data throughput needs.
Legal Services
EvenUp, San Francisco, CA, USA, Founded in 2019 — ($1.1 billion)
Employs AI to assist in the legal sector by automating document drafting, review and providing litigation support, particularly for personal injury cases. Target buyers include law firms, especially those dealing with high volumes of personal injury cases.
Everlaw, Oakland, CA, USA, Founded in 2011 — ($2 billion)
AI technology enhances legal discovery by providing advanced search, review, and analysis tools within its cloud-based platform, streamlining the eDiscovery process.Target buyers includelaw firms, corporate legal departments, and government agencies engaged in litigation.
Harvey, San Francisco, CA, USA, Founded in 2022 — ($1.5 billion)
Specializes in AI for legal services, offering automation in legal research, contract analysis, and client interaction through a chatbot interface. Target buyers include law firms, legal departments in corporations, and legal tech startups looking to automate routine legal tasks.
Mining & Mineral Exploration
KoBold Metals, Berkeley, CA, USA, Founded in 2018 — ($3 billion)
Uses AI to analyze geological data and discover critical mineral deposits, like copper and lithium, to support the energy transition. Target buyers imclude mining companies, renewable energy firms, and EV manufacturers.
Property & Premise Security
Ambient.ai, San Jose, CA, USA, Founded in 2016 — ($250 million)
Employs computer vision AI to analyze video feeds in real-time, providing proactive security through behavioral anomaly detection in physical spaces. Target buyers include commercial real estate, corporate campuses, and industries with high-security needs like finance and technology.
Intenseye, New York, NY, USA, Founded in 2018 — ($500 million)
Leverages AI for visual workplace safety analysis, detecting potential hazards and compliance issues through video analytics. Target buyers include manufacturing, construction, and logistics to enhance safety protocols.
Previoulsy a cofounder and chief scientist of OpenAI, Safe Superintelligence founder & CEO Ilya Sutskever’s says their sole focus is to develop safe superintelligence, the company’s only planned product.
Quantum Computing
Black Forest Labs, Freiburg, Germany, Founded in 2024 — ($1 billion+)
Innovates in quantum computing software, enabling more efficient problem-solving for complex calculations. Target buyers include finance and pharmaceuticals that require high computational power.
Focuses on creating AI with safety at its core, aiming for AI that's secure by design for high-stakes applications. Target buyers include governments, defense, and industries with stringent safety requirements.
SandboxAQ, Palo Alto, CA, USA, Founded in 2023 — ($5.6 billion)
Develops AI and quantum technologies for security and simulation, enhancing data protection and scientific research. Target buyers include cybersecurity, energy, and pharmaceutical companies.
Palmer Luckey, Founder & CEO of military AI startup Anduril previously sold Oculus to Facebook for $2 billion in 2014 and proves mullets are back in fashion.
Robots, Autonomous Vehicles & Drones
Anduril, Costa Mesa, CA, USA, Founded in 2017 — ($13 billion)
Develops AI-powered defense technology, including autonomous drones and surveillance systems, integrated through its Lattice software for real-time battlefield awareness. Target buyers include military and defense organizations, such as the U.S. Department of Defense and allied governments.
Helsing, Munich, Germany, Founded in 2021 — ($4 billion)
AI-driven software and recently pivoted to hardware with the HX-2 drone, enhancing military capabilities like radar systems and swarm-based combat operations. Target buyers include European militaries and defense contractors aiming to modernize with AI-enhanced systems.
Yang Zhilin, CEO of Beijing-based Moonshot AI, holds a PhD in computer science from Carnegie Mellon and also attended Tsinghua University and worked at Meta and Google Brain.
Moonshot AI, Beijing, China,Founded in 2023 — ($3.3 billion)
Works on AI for autonomous systems, with applications in robotic automation and self-driving technology. Target buyers include manufacturing and transportation industries.
Develops an AI-driven, mapless autonomous driving system using embodied AI to enable vehicles to learn and navigate real-world environments without predefined rules or HD maps. Target buyers include automotive OEMs like aiming to integrate advanced driver assistance and fully automated driving solutions.
Provides AI-powered sales automation tools to businesses to replace traditional sales software with digital workers for the entire Go-to-Market (GTM) sector. Target buyers include
6Sense, San Francisco, CA, USA, Founded in 2022 — ($5.2 billion)
Provides AI-powered predictive analytics for B2B sales and marketing, enabling precise account targeting and forecasting. Target buyers include B2B marketers, sales teams, and revenue operations professionals.
Ada, Toronto, Canada, Founded in 2021 — ($1.2 billion)
Specializes in AI-powered customer service automation, offering chatbots that handle customer inquiries with human-like interaction. Target buyers include customer service departments in various industries.
Aisera, Palo Alto, CA, USA, Founded in 2014 — ($2 billion)
Offers an AI service desk that automates IT support tasks, reducing response times and operational costs. Target buyers include IT departments across enterprises looking for efficient IT service management.
Amperity, Seattle, WA, USA, Founded in 2016 — ($1.1 billion)
Offers a customer data platform powered by AI to unify customer data, providing a 360-degree view for enhanced personalization in marketing and customer engagement. Target buyers include marketing and customer experience teams in retail, e-commerce, and consumer goods.
Decagon, San Francisco, CA, USA, Founded in 2023 — ($500 million)
Focuses on AI for software engineering, particularly in automating code review and quality assurance processes. Target buyers include software development teams in tech companies.
Kore.ai, Orlando, FL, USA, Founded in 2023 — ($1 billion)
Develops conversational AI platforms that enable businesses to create and deploy virtual assistants. Target buyers include businesses seeking to improve customer or employee engagement through AI.
Suki, Redwood City, CA, USA, Founded in 2013 — ($500 million)
Leverages AI for voice-enabled documentation, mainly in healthcare, to reduce the administrative burden on clinicians. Target buyers include healthcare providers, specifically hospitals and clinics.
Tractable, London, UK, Founded in 2014 — ($1 billion)
Applies AI to assess damage for insurance claims, speeding up claims processing with visual AI technology. Target buyers include insurance industry, particularly property and casualty insurers.
Social Media, Gaming, & Metaverse
AimLabs, New York City, NY, USA, Founded in 2017 — ($1 billion)
Leverages advanced AI algorithms to provide exact and adaptive training for gamers, enhancing their aiming and reaction skills through personalized drills and analytics. Its target buyers include competitive gamers and eSports teams seeking to improve performance.
ByteDance, San Francisco, CA, USA, Founded in 2023 — ($300 billion)
AI-driven content recommendation system, which personalizes user feeds across its platforms like TikTok and Douyin, significantly increasing user engagement and retention. Target buyers include advertisers looking to reach a broad, highly engaged audience and businesses seeking digital marketing solutions.
MiniMax, Shanghai, China,Founded in 2021 — ($3.1 billion)
Known for its large context window in its AI models, which allows for processing and understanding of vast amounts of text data, it utilizes this data in its chatbot services for more comprehensive and context-aware responses. Target buyers include businesses in need of advanced customer service automation and developers looking for robust AI language tools.
Suno, Campbell, CA, USA, Founded in 202 3— ($500 million)
Develops AI that creates soundscapes for various applications, from gaming to VR. Target buyers include entertainment industries looking for innovative sound design.
Synthesia, London, UK, Founded in 2017 — ($1 billion)
AI video avatar creation, which enables users to produce videos with virtual presenters who speak in multiple languages. This is ideal for content localization and personalized video messaging. Target buyers include marketers, educational content creators, and HR departments aiming to scale video production efficiently across different languages and regions.
Software Development Tools
Anysphere, San Francisco, CA, USA, Founded in 2022 — ($2.5 billion)
Offers AI-driven code generation, aiming to automate parts of software development with tools like Cursor, which helps write code faster. Target buyers include software developers and tech companies interested in improving development efficiency.
Augment Code, Palo Alto, CA, USA, Founded in 2022 — ($1 billion)
Uses AI to enhance software development processes, focusing on auto-suggestions for coding and debugging and aiming to increase developer productivity. Target buyers include software developers and tech teams looking to accelerate development cycles.
Codeium, Mountain View, CA, USA, Founded in 2021 — ($1.3 billion)
Provides AI-assisted code completion and generation, enhancing developer productivity by suggesting code in real-time. Target buyers include developers and software teams across various industries looking to boost coding efficiency.
Cognition AI, San Francisco, CA, USA, Founded in 2023 — ($2 billion)
AI focuses on developing cognitive computing platforms that mimic human thought processes for decision-making and problem-solving. Target buyers include industries like finance, healthcare, and logistics for complex decision support systems.
Cursor, San Francisco, CA, USA, Founded in 2022 — ($2.5 billion)
Develops an AI-powered code editor that enhances developer productivity by predicting, writing, and editing code with real-time assistance, built as a customized fork of VS Code. Target buyers include individual developers and enterprise tech firms.
Datarobot founder & CEO Jeremy Achin, previously worked at Travelers Insurance where he built predictive models for the insurance business.
Datarobot, Boston, MA, USA, Founded in 2023 — ($6.3 billion)
Automates the end-to-end process of data science, from data prep to model deployment, facilitating AI and machine learning for businesses without extensive data teams. Target buyers include mid to large enterprises across various sectors that want to leverage AI.
Poolside, Paris, France, Founded in 2023 — ($3 billion)
Poolside innovates with AI models designed to automate and enhance software development, offering tools like intelligent code assistants to revolutionize coding. Target buyers include software developers, large enterprises, and public-sector agencies seeking to improve productivity and efficiency in coding and software creation.
Replit, San Francisco, CA, USA, Founded in 2016 — ($1.2 billion)
Offers an online IDE for collaborative coding with integrated AI assistance for coding, debugging, and learning. Target buyers include students, educators, and developers seeking a cloud-based development environment.
Pachama founder & CEO Diego Saez-Gil was raised in the north of Argentina, at the foothills of the Andes and the Yunga forests.
Sustainability
Pachama, San Francisco, CA, USA, Founded in 2023 — ($371 million)
Leverages AI and satellite imagery to verify and monitor forest carbon sequestration, offering a transparent marketplace for high-quality carbon credits. Target buyers include corporations, individuals and project developers seeking to meet net-zero goals.
World Labs, Stanford, CA, USA, Founded in 2024 — ($1 billion+)
Focuses on AI for global problem-solving, particularly in climate and health, with models tailored for these applications. Target buyers include NGOs, governments, and R&D in related fields.
So there you have it! Again, we are presenting our readers this early look at our AI company list so you can tell us the names of companies we might be missing.
Please email us with any confidential input and company recommendations to theeditor@cryptoniteventures.com 😎🙏🏼
Next post: We will introduce out top company picks in robotics, autonomous & electric vehicles, and drones—Stay tuned!
Keep the eyes of over 520,000 global innovators on your brand here. Contact tom@cryptoniteventures.com and make it happen!
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