Latest news with #HarrisonChase
Forbes
09-07-2025
- Business
- Forbes
AI Startup LangChain Is In Talks To Raise $100 Million
Programming with ChatGPT dpa/picture alliance via Getty Images L angChain, whose AI software helps developers build applications using models like OpenAI's GPT-4, has raised $100 million in funding at a $1.1 billion valuation, four sources familiar with the deal told Forbes . VC outfit IVP is leading the round, the sources said. The company, which was on the 2025 Forbes AI 50 list and on the 2024 Forbes Next Billion Dollar Startups List, has about $16 million in annualized revenue, two of the source said. LangChain did not respond to Forbes' request for comment. IVP declined to comment. The funding amount has not been previously reported. TechCrunch first broke news of the deal. Cofounders Harrison Chase and Ankush Goyal started LangChain in 2023 as an open source software that helped engineers quickly spin up AI-powered apps with as little as a few dozen lines of code. The platform has been used to build generative AI-based tools that can do everything from legal document review to retail refund processing. The company's first product LangSmith helps developers evaluate, monitor and debug code, helping businesses quickly ship products while ensuring the models perform accurately and provide relevant answers. It is used by some 40,000 teams at tech giants like Uber and LinkedIn as well as buzzy AI startups like Mercor and Lovable. In early 2024, the company introduced a new tool called LangGraph to help businesses build AI 'agents' capable of performing specific tasks on their own. The tools have more than 20 million monthly downloads, according to the company's website. The round follows a $20 million Series A round in February 2024 led by Sequoia at a $200 million valuation. Langchain's other backers include top VCs like Benchmark, Conviction and Lux Capital. As more AI startups dedicate resources to creating apps or features that target sectors like healthcare, engineering or finance, LangChain is well positioned to sell its suite of tools to developers. But it'll have to watch out for AI coding tools like Cursor and Windsurf and website development apps like Lovable that help companies save time and money while automating the process of integrating AI into everything they do. Forbes Legal AI Startup Legora In Talks To Raise New Funding At A $675 Million Valuation By Rashi Shrivastava Forbes AI Startup Decagon In Talks To Raise $100 Million At A $1.5 Billion Valuation By Rashi Shrivastava Forbes Two Y Combinator Partners Are Leaving To Start A New Series A Fund By Richard Nieva
Yahoo
08-07-2025
- Business
- Yahoo
LangChain is about to become a unicorn, sources say
LangChain, an AI infrastructure startup providing tools to build and monitor LLM-powered applications, is raising a new round of funding at an approximate $1 billion valuation led by IVP, according to three sources with knowledge of the deal. LangChain began its life in late 2022 as an open-source project founded by Harrison Chase, who was then an engineer at machine learning startup Robust Intelligence. After generating significant developer interest, Chase transformed the project into a startup, securing a $10 million seed round from Benchmark in April 2023, That round was followed a week later by a $25 million Series A led by Sequoia, reportedly valuing LangChain at $200 million. The startup was an early darling of the AI era. When LangChain first emerged, LLMs lacked access to real-time information and the ability to perform actions such as searching the web, calling APIs, and interacting with databases. The startup's open-source code solved those problems with a framework for building apps on top of LLMs models. It became a hugely popular project on GitHub (111K stars, over 18,000 forks). The LLM ecosystem has since expanded significantly, with new startups including LlamaIndex, Haystack, and AutoGPT now offering comparable features. Furthermore, leading LLM providers including OpenAI, Anthropic, and Google have evolved their APIs to directly offer capabilities that were once key differentiators for LangChain's core technology. So the company has added other products, including LangSmith, a separate, closed-source product for observability, evaluation, and monitoring of LLM applications, specifically agents. This product has soared in popularity, multiple people tell us. Since its introduction last year, LangSmith has led the company to reach annual recurring revenue (ARR) between $12 million and $16 million, four sources told TechCrunch. The company didn't respond to a request for comment. Developers can start working with LangSmith for free and upgrade to $39 per month for small team collaboration features, according to the company's website. LangChain also offers custom plans for large organizations. Companies who use LangSmith include Klarna, Rippling, and Replit. While LangSmith currently leads the burgeoning LLM operations space, it does have competitors like smaller, open-source Langfuse and Helicone. IVP declined to comment on this report. Error while retrieving data Sign in to access your portfolio Error while retrieving data Error while retrieving data Error while retrieving data Error while retrieving data
TechCrunch
08-07-2025
- Business
- TechCrunch
LangChain is about to become a unicorn, sources say
LangChain, an AI infrastructure startup providing tools to build and monitor LLM-powered applications, is raising a new round of funding at an approximate $1 billion valuation led by IVP, according to three sources with knowledge of the deal. LangChain began its life in late 2022 as an open-source project founded by Harrison Chase, who was then an engineer at machine learning startup Robust Intelligence. After generating significant developer interest, Chase transformed the project into a startup, securing a $10 million seed round from Benchmark in April 2023, That round was followed a week later by a $25 million Series A led by Sequoia, reportedly valuing LangChain at $200 million. The startup was an early darling of the AI era. When LangChain first emerged, LLMs lacked access to real-time information and the ability to perform actions such as searching the web, calling APIs, and interacting with databases. The startup's open-source code solved those problems with a framework for building apps on top of LLMs models. It became a hugely popular project on GitHub (111K stars, over 18,000 forks). The LLM ecosystem has since expanded significantly, with new startups including LlamaIndex, Haystack, and AutoGPT now offering comparable features. Furthermore, leading LLM providers including OpenAI, Anthropic, and Google have evolved their APIs to directly offer capabilities that were once key differentiators for LangChain's core technology. So the company has added other products, including LangSmith, a separate, closed-source product for observability, evaluation, and monitoring of LLM applications, specifically agents. This product has soared in popularity, multiple people tell us. Since its introduction last year, LangSmith has led the company to reach annual recurring revenue (ARR) between $12 million and $16 million, four sources told TechCrunch. The company didn't respond to a request for comment. Developers can start working with LangSmith for free and upgrade to $39 per month for small team collaboration features, according to the company's website. LangChain also offers custom plans for large organizations. Companies who use LangSmith include Klarna, Rippling, and Replit. Techcrunch event Save up to $475 on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Save $450 on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Boston, MA | REGISTER NOW While LangSmith currently leads the burgeoning LLM operations space, it does have competitors like smaller, open-source Langfuse and Helicone. IVP declined to comment on this report.
Geeky Gadgets
23-05-2025
- Business
- Geeky Gadgets
Interrupt 2025 Keynote with Harrison Chase from LangChain
What does it take to transform the way we interact with technology? At Interrupt 2025, Harrison Chase, co-founder of LangChain, delivered a keynote that painted a vivid picture of the future of AI agents—one where intelligent systems seamlessly integrate into our workflows, amplifying human potential. From its humble beginnings as an open source project to its current role as a trailblazer in AI development, LangChain has redefined how developers approach the creation of production-ready AI agents. Chase's presentation didn't just highlight the technical strides made by LangChain; it underscored the emergence of a new kind of professional—the 'agent engineer'—tasked with bridging the gap between innovative AI models and real-world applications. It's a vision of the future that feels both inevitable and exhilarating. In this perspective, LangChain unpack the fantastic ideas shared during Chase's keynote, exploring the evolution of LangChain, the tools allowing developers to build scalable agents, and the trends shaping the future of AI. From the widespread access of agent-building to the rise of collaborative platforms like LangSmith and LangGraph, Chase's insights offer a roadmap for navigating the challenges of deploying intelligent systems. Whether you're a developer, a tech enthusiast, or someone curious about the next frontier of AI, this exploration promises to illuminate the possibilities—and the hurdles—that lie ahead. After all, the story of LangChain is not just about technology; it's about reimagining how humans and machines can work together. LangChain's AI Agent Evolution The Evolution of LangChain LangChain began as an open source initiative designed to help developers prototype AI applications. Over time, it evolved into a company focused on addressing the complexities of scaling these prototypes into robust, production-ready systems. The mission is straightforward yet ambitious: to make intelligent agents a ubiquitous part of modern technology by building reliable tools around LLMs. This transformation reflects the growing demand for solutions that bridge the gap between experimentation and real-world deployment, a critical challenge in the AI ecosystem. The shift from a prototyping tool to a comprehensive platform underscores LangChain's commitment to allowing developers to create scalable, reliable, and impactful AI agents. By addressing the technical and operational challenges of deploying AI systems, LangChain is positioning itself as a key player in the AI development landscape. Core Components of Building AI Agents Developing effective AI agents requires expertise across multiple domains. Harrison Chase emphasized four critical components that form the foundation of this process: Prompting: Crafting precise and effective prompts to optimize the performance of LLMs, making sure they generate accurate and contextually relevant outputs. Crafting precise and effective prompts to optimize the performance of LLMs, making sure they generate accurate and contextually relevant outputs. Engineering: Building robust tools, data pipelines, and deployment strategies to ensure agents operate seamlessly in real-world environments. Building robust tools, data pipelines, and deployment strategies to ensure agents operate seamlessly in real-world environments. Product Design: Translating user workflows and needs into AI-driven solutions that are intuitive and practical. Translating user workflows and needs into AI-driven solutions that are intuitive and practical. Machine Learning: Using evaluation metrics and fine-tuning techniques to enhance the performance and reliability of AI agents. These components collectively define the emerging role of the 'agent engineer,' a position that combines technical expertise with a deep understanding of user-centric design. This interdisciplinary approach is essential for creating AI agents that are not only functional but also scalable and user-friendly. Interrupt 2025 Keynote Watch this video on YouTube. Find more information on LangChain by browsing our extensive range of articles, guides and tutorials. The Emergence of the 'Agent Engineer' The 'agent engineer' is a pivotal new role in the AI development landscape, combining skills in prompting, engineering, product design, and machine learning. LangChain has developed tools specifically to empower these professionals, allowing them to build agents that are both reliable and scalable. This role highlights the interdisciplinary nature of AI development, requiring a blend of technical proficiency and design acumen. By equipping agent engineers with the right tools, LangChain is fostering a new generation of developers capable of addressing the unique challenges of AI agent creation. This role is expected to become increasingly important as the demand for intelligent, production-ready agents continues to grow across industries. The Current State and Future Potential of AI Agents Harrison Chase provided valuable insights into the current state of AI agents and the trends shaping their future development. He identified several key principles that are driving advancements in this field: Model Diversity: Future AI agents will use multiple LLMs, each optimized for specific tasks, to handle complex workflows more effectively. Future AI agents will use multiple LLMs, each optimized for specific tasks, to handle complex workflows more effectively. Context Engineering: Precise control over input context is critical for creating reliable and effective agents capable of managing diverse scenarios. Precise control over input context is critical for creating reliable and effective agents capable of managing diverse scenarios. Collaboration: The development of AI agents is inherently a team effort, requiring tools and platforms that accommodate diverse skill sets and expertise. These principles emphasize the importance of flexibility, precision, and teamwork in advancing AI agent technology. As the field evolves, these factors will play a crucial role in shaping the capabilities and applications of intelligent agents. LangChain's Tools and Platforms To address the challenges of building and deploying AI agents, LangChain has introduced a suite of tools and platforms designed to streamline the development process. These include: LangGraph: A low-level framework for agent orchestration, providing developers with flexibility and control over agent workflows. A low-level framework for agent orchestration, providing developers with flexibility and control over agent workflows. LangSmith: A platform for observability, evaluation, and collaboration, allowing teams to monitor and refine their agents effectively. A platform for observability, evaluation, and collaboration, allowing teams to monitor and refine their agents effectively. LangGraph Studio V2: An upgraded interface for modifying and debugging agents, offering enhanced usability and functionality. An upgraded interface for modifying and debugging agents, offering enhanced usability and functionality. Open Agent Platform: A no-code, open source platform that allows both developers and non-developers to build intelligent agents. A no-code, open source platform that allows both developers and non-developers to build intelligent agents. LangGraph Platform: A deployment solution tailored for long-running, bursty, and stateful agents, addressing scalability and operational challenges. These tools are designed to meet the unique needs of AI agent development, from debugging and evaluation to scalability and deployment. By providing a comprehensive suite of solutions, LangChain is allowing developers to overcome the technical and operational hurdles of AI agent creation. Trends and Challenges Shaping the Future Harrison Chase outlined several trends and challenges that will define the future of AI agents. These include: AI Observability: Developing new metrics and methodologies to evaluate agent performance and address unique challenges in this domain. Developing new metrics and methodologies to evaluate agent performance and address unique challenges in this domain. Widespread access of Agent Building: Creating tools that empower both developers and non-developers to build intelligent agents, making the technology more accessible. Creating tools that empower both developers and non-developers to build intelligent agents, making the technology more accessible. Deployment Challenges: Addressing issues such as scalability, statefulness, and the integration of human-in-the-loop interactions to enhance agent reliability and effectiveness. These focus areas highlight the ongoing efforts to make AI agents more accessible, reliable, and impactful in real-world applications. As the technology matures, these challenges will need to be addressed to unlock the full potential of intelligent agents. Industry Adoption and Growth AI agents are rapidly gaining traction across industries, with significant adoption in areas such as customer support, AI-powered search, and Copilot applications. Harrison Chase noted that 2024 marked the beginning of widespread adoption, with 2025 poised to see even greater growth. As organizations increasingly integrate AI agents into their operations, the demand for tools, expertise, and skilled professionals in this field is expected to rise significantly. LangChain's focus on empowering developers and organizations with the tools and knowledge needed to build intelligent agents positions it as a leader in this rapidly evolving industry. The insights shared during Chase's keynote provide a roadmap for navigating the challenges and opportunities of AI agent development, offering valuable guidance for those looking to harness the power of this fantastic technology. Media Credit: LangChain Filed Under: AI, Top News Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
