Latest news with #LangChain
Forbes
5 hours ago
- 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
a day ago
- 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
a day ago
- 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
a day ago
- Business
- Geeky Gadgets
LangGraph Assistants : Build Reusable Configurable AI Agents
What if creating a powerful AI agent was as simple as adjusting a few settings, without ever touching the underlying code? The rise of LangGraph Assistants is turning this vision into reality, offering a new approach to AI development that prioritizes flexibility and efficiency. By separating architecture from configuration, LangGraph Assistants empower developers and businesses to customize AI agents for vastly different tasks—whether it's generating social media content or performing financial analysis—without the need for extensive redevelopment. This shift not only reduces complexity but also opens the door to unprecedented scalability in AI applications, making it easier than ever to adapt to evolving demands. In this report, LangChain explain how LangGraph Assistants are redefining what's possible in AI agent development. From their innovative decoupling of architecture and configuration to the intuitive tools provided by LangGraph Studio, these assistants are designed to streamline customization, experimentation, and deployment. You'll discover how their future-proof design enables rapid adaptation to shifting requirements and why their versatility makes them indispensable across industries. Whether you're a developer aiming to optimize workflows or a business leader seeking scalable AI solutions, LangGraph Assistants offer a glimpse into the future of configurable AI. Could this be the key to unlocking AI's full potential? LangGraph Assistants Overview The Value of Separating Architecture from Configuration The central innovation of LangGraph Assistants lies in decoupling the agent's architecture—its foundational structure and logic—from its configuration, which includes prompts, models, and tools. This separation introduces several key advantages: Adaptability: A single architecture can be repurposed for different tasks or teams by simply adjusting configurations, eliminating the need for extensive redevelopment. A single architecture can be repurposed for different tasks or teams by simply adjusting configurations, eliminating the need for extensive redevelopment. Efficiency: Switching between use cases no longer requires code modifications, saving time and reducing complexity. Switching between use cases no longer requires code modifications, saving time and reducing complexity. Flexibility: For example, the same agent can be configured to handle tasks as diverse as social media content creation or financial analysis. This approach allows you to focus on achieving desired outcomes without being constrained by technical limitations, making sure that your AI agents remain versatile and future-proof. Streamlined Customization and Experimentation LangGraph Assistants are designed to make customization and experimentation straightforward and efficient. This capability is particularly valuable in dynamic environments where requirements frequently change. Rapid Testing: Developers can experiment with new configurations without redeploying the codebase, significantly reducing development cycles. Developers can experiment with new configurations without redeploying the codebase, significantly reducing development cycles. User-Friendly Interfaces: Business teams can easily tailor agents to specific needs using intuitive tools, eliminating the need for deep technical expertise. For instance, if market trends or user preferences shift, you can quickly adapt an assistant to reflect these changes without disrupting its core functionality. This ensures that your AI agents remain relevant and effective, even in rapidly evolving industries. What Are LangGraph Assistants? The Future of Configurable AI Explained Watch this video on YouTube. Below are more guides on AI Agents from our extensive range of articles. LangGraph Studio: A Visual IDE for AI Innovation LangGraph Studio serves as a visual integrated development environment (IDE), simplifying the creation, testing, and management of AI agents. Its robust set of tools enables developers and business users alike to optimize their AI solutions with ease. Key features include: Instant Configuration Changes: Modify agent settings in real time to meet specific requirements. Modify agent settings in real time to meet specific requirements. Performance Monitoring: Track agent performance metrics to ensure optimal functionality. Track agent performance metrics to ensure optimal functionality. Version Control: Safely experiment with new configurations while maintaining the ability to revert to previous versions if needed. For example, if you're developing a sports writing assistant, LangGraph Studio allows you to adjust its tone, style, or data sources to cater to different audiences with just a few clicks. By removing technical bottlenecks, LangGraph Studio enables you to focus on innovation and user experience. Enterprise-Grade Deployment with LangGraph Platform The LangGraph Platform is tailored for enterprise-level AI deployments, offering advanced features that ensure reliability, scalability, and control. These capabilities are particularly beneficial for organizations managing complex AI ecosystems. Key functionalities include: Robust Versioning: Maintain detailed version histories and rollback capabilities to mitigate risks during updates. Maintain detailed version histories and rollback capabilities to mitigate risks during updates. A/B Testing: Optimize agent configurations by comparing performance across different setups. Optimize agent configurations by comparing performance across different setups. Scalability: Seamlessly manage multi-agent systems, making sure consistent performance across large-scale deployments. Whether you're deploying a single assistant or a network of specialized agents, the LangGraph Platform integrates seamlessly into existing workflows. This ensures that your AI solutions can scale alongside your organization's growth while maintaining operational efficiency. Programmatic Management with SDKs and APIs LangGraph Assistants also support programmatic management through SDKs and APIs, allowing seamless integration with your existing infrastructure. These tools provide several advantages: Automation: Automate the creation, updating, and management of AI agents to streamline operations. Automate the creation, updating, and management of AI agents to streamline operations. CI/CD Integration: Incorporate agents into continuous integration and deployment pipelines for efficient testing and deployment. Incorporate agents into continuous integration and deployment pipelines for efficient testing and deployment. Agility: Ensure that agents remain responsive to evolving requirements by automating configuration updates. For example, a customer support assistant can be updated with a new configuration to address emerging user needs, making sure minimal downtime and maximum efficiency. This programmatic approach enhances the scalability and responsiveness of your AI systems. Version Control: Making sure Safe Experimentation LangGraph Assistants incorporate a robust version control system that tracks every configuration change. This feature is particularly valuable for managing complex multi-agent systems with diverse configurations. Benefits include: Localized Customization: Deploy assistants with market-specific configurations, such as tailoring a financial analysis agent for different regions. Deploy assistants with market-specific configurations, such as tailoring a financial analysis agent for different regions. Risk Mitigation: Roll back to previous versions if a new configuration fails to meet expectations. This system ensures that your AI agents remain reliable and adaptable, even as requirements evolve. By allowing safe experimentation, LangGraph Assistants empower you to innovate without compromising stability. Versatility Across Diverse Applications LangGraph Assistants are designed to excel in a wide range of applications, making them suitable for various industries and tasks. Whether you need an assistant for: Social media content creation, Financial analysis, Sports writing, Or other specialized tasks, the platform allows you to configure and deploy tailored solutions quickly. Switching between assistants is seamless, making sure that your AI tools remain effective across diverse scenarios. This versatility makes LangGraph Assistants a valuable asset for organizations seeking to use AI in innovative ways. Media Credit: LangChain Filed Under: AI, Technology 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.
Geeky Gadgets
02-07-2025
- Business
- Geeky Gadgets
Build AI Apps with Secure Logins and Payments with LangGraph.js in Minutes
Have you ever wondered how some of the most seamless apps handle secure logins, process payments, and track user activity—all without breaking a sweat? Building such a system might seem like a daunting task, but with the right tools and approach, it's more accessible than you think. Enter a powerful framework that allows developers to create intelligent agents while integrating essential features like authentication and payments. Whether you're crafting a personal side project or launching a scalable commercial platform, mastering these integrations is the key to delivering a polished, user-friendly experience. And the best part? You don't need to start from scratch. In this LangChain quick-start guide, you'll learn how to combine with tools like Supabase, Stripe, and React to build an agent that's not only secure but also scalable and efficient. From implementing robust authentication systems to streamlining payment processing and credit tracking, this guide covers the essentials to help you create a platform that feels professional and intuitive. Along the way, you'll discover how to use Supabase JWT tokens to safeguard sensitive operations, use Stripe's API for seamless transactions, and manage user credits with ease. By the end, you'll have the foundation for a system that balances functionality with security—an achievement every developer can be proud of. Building a Full-Stack App Authentication: Establishing a Secure Foundation Authentication is the cornerstone of any secure application. Supabase simplifies this process by offering a robust authentication system that supports essential features such as user login, logout, and session management. Its scalability and reliability make it an ideal choice for modern applications. To secure your agent, middleware can validate Supabase JWT tokens. These tokens ensure that only authenticated users can access the agent, safeguarding sensitive operations. Additionally, configuration files allow you to define user permissions and bind metadata, allowing role-based access control. This ensures that users only access features and data relevant to their roles, enhancing both security and user experience. Streamlining Payment Integration with Stripe Stripe is a versatile tool for managing payments in your application, offering features that cater to both subscription-based and usage-based systems. Its API supports seamless integration, allowing you to handle tasks such as: Creating checkout sessions for new users or one-time purchases for new users or one-time purchases Managing subscriptions for recurring payments for recurring payments Updating user credits for usage tracking To maintain synchronization between your application and Stripe, webhook routes are essential. These routes process events such as subscription updates, cancellations, and credit purchases. By implementing these webhooks, you ensure that your application remains up-to-date with user payment statuses, providing a smooth and reliable experience. Guide to Using for Authentication and Payments Watch this video on YouTube. Discover other guides from our vast content that could be of interest on Credit Management: Tracking and Optimizing Usage A robust credit management system is vital for tracking user activity and making sure fair usage of your application. By storing credit data in Supabase, you centralize and secure this information, making it easier to manage and scale. Optimistic UI updates further enhance the user experience by providing immediate feedback, even before database synchronization is complete. Utility functions simplify credit-related operations, including: Adding credits to user accounts to user accounts Refreshing balances to reflect the latest usage to reflect the latest usage Deducting credits for specific actions or services This approach ensures that your application remains responsive and user-friendly, even during periods of high demand. By integrating credit management seamlessly into your system, you create a transparent and efficient usage tracking mechanism. Building the Chat Agent and Enhancing the User Interface The agent, developed using React and TypeScript, serves as the core of your application. This agent can be enhanced with web search capabilities using tools like Tabi, which expand its functionality and provide users with more comprehensive results. Providers such as Thread and Stream manage conversation data, making sure smooth and efficient interactions. To maintain security, Supabase JWT tokens are passed to the LangGraph middleware. This ensures that only authenticated users can interact with the agent, preserving the integrity of your application. By combining these tools, you create a responsive and secure chat agent that meets the needs of your users. Organizing Your Codebase for Efficiency A well-structured codebase is essential for efficient development and maintenance. Adopting a monorepo approach allows you to organize your project into two main applications: Agents Repository: This contains the agent and middleware for authentication, making sure that the core functionality is modular and easy to manage. This contains the agent and middleware for authentication, making sure that the core functionality is modular and easy to manage. Web Application: This includes the user interface, Stripe integration, Supabase authentication, and credit management system, providing a cohesive and user-friendly experience. Comprehensive documentation is a critical component of a well-organized codebase. A detailed README file should guide developers through the setup process, explaining key files and configurations. This not only simplifies onboarding for new team members but also makes it easier to customize and extend the application as needed. Setting Up and Customizing Your Application Getting started with your application involves configuring the repository and integrating the necessary tools. A step-by-step setup guide ensures that you can quickly deploy the application, while its modular design allows for easy customization. Whether you are building a personal project or a commercial platform, this approach provides the flexibility to adapt to your specific requirements. Customization options include modifying the user interface, adjusting credit management rules, or integrating additional features such as analytics or third-party APIs. By using the modularity of Supabase, and Stripe, you can tailor the application to meet the unique needs of your users. Creating a Secure and Scalable Platform By combining with Supabase, Stripe, and React, you can build a full-stack application that is both secure and scalable. Each component plays a critical role in delivering a seamless experience for your users. From authentication to payment processing and credit management, these tools work together to create a robust and user-friendly platform. A well-organized codebase and thorough documentation further enhance the development process, making it easier to maintain and expand your application. With this approach, you are equipped to create a platform that meets the demands of modern users while providing the flexibility to grow and evolve over time. Media Credit: LangChain Filed Under: Gadgets 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.
