Ollama has successfully raised $65 million in a Series B funding round. These funds are intended to strengthen the company's position within the growing ecosystem of open artificial intelligence.
Ollama has successfully raised $65 million in a Series B funding round. These funds are intended to strengthen the company's position within the growing ecosystem of open artificial intelligence.
The round was led by Theory Ventures, with participation from investors such as Benchmark, 8VC, Y Combinator, Pace Capital, 49 Palms, and GTMFund. According to the company's statement, the received investments will be directed towards further product development, expanding cloud capabilities, and hiring new employees.
Ollama, co-founded by Jeffrey Morgan and Michael Chiang, is an open-source platform that allows developers to run large language models directly on their local devices. The platform is available for Mac, Windows, and Linux operating systems. Furthermore, developers can upload workloads to the Ollama cloud without needing to change existing workflows. This approach has helped Ollama become one of the largest platforms for working with open-source models.
Ollama has experienced accelerated growth over the past year. Currently, the platform serves 8.9 million active monthly developers and boasts over 67,000 community-created integrations. Platform usage has doubled since January, with nearly a million new installations added weekly. The company also reports the adoption of its solutions in 85% of Fortune 500 organizations, including enterprises in the healthcare, finance, and public administration sectors.
Developers use Ollama to simplify AI deployment while maintaining privacy and performance. With sufficient hardware, models can run locally, and larger tasks automatically scale to the Ollama cloud via a unified interface. The company confirms that customer data is never used to train its AI models, making the platform attractive to regulated industries.
Ollama has established partnerships with leading global AI model developers such as Meta, Google DeepMind, Mistral, and MiniMax. The company also collaborates with hardware providers, including NVIDIA, Intel, AMD, and Qualcomm. These connections provide developers with early access to new models and improved hardware performance.
CEO Jeffrey Morgan emphasized that open models must remain simple to develop and accessible where developers prefer to work. He stated the company's commitment to supporting the open-source community, adding that the future of AI will depend on open models running both on local devices and in the cloud environment.
Tomasz Tunguz, General Partner at Theory Ventures, believes that platforms like Ollama will become essential infrastructure for the next generation of AI software. He noted that more specialists are creating their own AI-based workflows, increasing the demand for accessible development platforms.
The Series B funding has provided Ollama with additional resources to expand its cloud presence and continuously improve developer tools. The company also plans to hire key specialists in engineering and product teams. These investments should help Ollama manage the growing interest in its services, especially from corporate clients alongside independent developers. With millions of users and leading venture capitalists, Ollama is poised for future success.
Mowito, a company specializing in physical artificial intelligence (AI) and creating foundational models for industrial robots, announced on Tuesday that it has raised $3 million in a seed funding round.
The round was led by Version One Ventures. Other participants included All In Capital, Unisol, iSeed, as well as angel investors such as Soumith Chintala (from Thinking Machines Lab), Adarsh Kulkarni (from Foundry Robotics), Ashish Kulkarni (from Coformer.ai), and Vaibhav Domkundwar (from Better Capital).
The company stated that the funds will be used to accelerate expansion in the United States, strengthen engineering and market teams, and scale deployments with manufacturers in the automotive and electronics industries.
Founded in 2024, Mowito develops physical AI models that allow industrial robots to learn directly from task demonstrations. This eliminates the need for traditional programming while maintaining the necessary precision for manufacturing processes.
The company serves global manufacturers in the automotive and electronics sectors, with headquarters in Bengaluru and Detroit. It was noted that Mowito robots are already being used on production lines of a major Fortune 500 automotive company and one of the world's largest electronics contract manufacturers, supporting high-precision assembly operations.
Co-founder and CEO of Mowito, Puru Rastog, emphasized that manufacturing has reached a point where the bottleneck is no longer hardware but software. He noted that robots should not require reprogramming when production changes, but should learn like humans—through observation and repetition. He added that this funding will help accelerate this concept, expand globally, and implement Physical AI in more manufacturing environments.
All In Capital Partner Kushal Bhagia expressed the view that manufacturing is entering a new phase where AI will radically change industrial automation. He highly praised Mowito, stating that the company is creating fundamental technology that removes one of the main barriers to industrial automation—the complexity of robot programming—and that the technical depth of the team, early customer validation, and vision for Physical AI place it in an exceptional position to define this category.
Yotta Data Services, a company specializing in artificial intelligence infrastructure and data centers, announced the raising of approximately $150 million from non-institutional investors. The company's valuation was set at approximately 37,000 crore rupees.
The raised capital is intended to strengthen the company's financial position through growth and to support the next stage of expansion. The company emphasized that all attracted funds will be directed towards accelerating growth, and there was no Offer for Sale (OFS) from shareholders in this round.
Yotta continues to assess interest from long-term institutional investors while maintaining its course toward its pre- and post-IPO plan, although the timeline for this has not been disclosed. Previously, there were reports that the company was raising funds through global funds or via listing.
The company stated that its current valuation is based on fundamental business metrics, revenue from long-term contracts, and execution visibility. Yotta expects this valuation to increase as its AI infrastructure capacity grows and new client agreements are signed.
Operationally, Yotta plans to increase its AI cloud platform to over 40,000 Nvidia Blackwell GPUs within the next four months, and to approximately 85,000 GPUs by the end of the current fiscal year. This will enable it to become one of the largest AI computing platforms outside the US and China.
The company continues to support sovereign cloud and AI initiatives in India while scaling up services for global AI model developers and inference providers. Yotta's long-term goal is to help India become a producer of AI infrastructure and intelligence, rather than just a consumer.
LinqAlpha has successfully raised $22 million in a Series A funding round. These funds are earmarked to accelerate the growth of its artificial intelligence platform designed for institutional investors.
The round was supported by investors such as AVP, Atinum Investment, and GFT Ventures. Additionally, several strategic financial institutions and venture platforms from Europe, Asia, and the United States participated. The New York-based company develops what it calls the Alpha Intelligence Layer for global public markets.
The platform assists investment specialists in processing complex market information using specialized AI agents. With this new funding, LinqAlpha's total raised capital has increased to approximately $28.6 million.
LinqAlpha was founded in 2022 by Jacob Choi, Subin Pang, Jin Kim, and Hodjun Choi. The founding team combines financial expertise with research in artificial intelligence. Among the founders are former Goldman Sachs analysts and MIT computer science graduates.
As public markets become increasingly interconnected, investors are forced to simultaneously track earnings reports, policy changes, supply chain events, credit markets, and social media signals. LinqAlpha believes that traditional analysis methods cannot keep up with such a growing volume of data. The platform allows investment teams to use AI agents trained on their own research history instead of relying on general language models. These agents then link new market events to previous investment ideas to generate relevant insights. One of the founders noted that the competitive advantage lies in identifying market-influencing signals even before they become widely known.
Currently, the platform is used by over 70 financial institutions. Clients include research, trading, and sales teams at major investment banks. On the buying side, clients include Causeway Capital Management LLC and Schonfeld Strategic Advisors LLC. The company initially started in Cambridge, Massachusetts, and later operated between South Korea and the United States before establishing its headquarters in New York. During this period, the business also underwent two rebrandings before adopting the name LinqAlpha.
The new funding will allow the company to expand its international staff. Management also plans to strengthen integration with market and alternative datasets. Additional investments will be directed towards implementing equity, macroeconomics, credit, and multi-asset investment strategies.
LinqAlpha is entering the competitive market of AI research platforms. Demand continues to grow as investment firms seek faster analysis without compromising their proprietary insights. According to Manish Agarwal, General Partner at AVP, many AI products focus on automating routine tasks or accelerating information retrieval. He believes that LinqAlpha helps investors find differentiated investment ideas through context-aware intelligence.
Competition remains significant, as large AI service providers have attracted significantly more funding in recent years. Nevertheless, LinqAlpha asserts that its specialized approach better meets the needs of institutional investors who seek bespoke analysis rather than standard AI outputs. Industry forecasts also point to continued expansion in financial AI, with growing adoption among banks, insurance companies, and asset managers expected to attract further investment in companies developing specialized corporate AI platforms. LinqAlpha's long-term success will likely depend on demonstrating measurable value to institutional clients operating in increasingly complex global markets.
