By Nuno Campos and Vadym Barda Over the past year, we’ve invested heavily in making LangGraph the go-to framework for building AI agents. With companies like Replit, Klarna, LinkedIn and Uber choosing to build on top of LangGraph, we have more conviction than ever that we are on

See how MUFG Bank used LangChain to streamline corporate sales research, cutting data analysis time from hours to minutes and boosting efficiency 10x.

Evaluations (evals) are important for bringing reliable LLM powered applications or agents to production, but it can be hard to know where to start when building evaluations from scratch. Our new packages—openevals and agentevals—provide a set of evaluators and a common framework that you can easily

Editor's note: this is a guest post from our friends at Onyx. As LangGraph has matured, we've seen more and more companies (Klarna, Replit, AppFolio, etc) start to use it as their agent framework of choice. We thought this was a great blog describing in detail

Today we're releasing the LangMem SDK, a library that helps your agents learn and improve through long-term memory. It provides tooling to extract information from conversations, optimize agent behavior through prompt updates, and maintain long-term memory about behaviors, facts, and events. You can use its core API with

Klarna's AI assistant is revolutionizing the personal shopping experience, including customer service and productivity. See how they used LangGraph and LangSmith to achieve 80% faster customer resolution times.

We explore how increasing the number of instructions and tools available to a single ReAct agent affects its performance, benchmarking models like claude-3.5-sonnet, gpt-4o, o1, and o3-mini across two domains of tasks.

Vizient's GenAI platform helps users manage data to query for information ranging from patient outcomes to clinical benchmarking. See how they used LangGraph and LangSmith for multi-agent system reliability and prompt management.

See how Infor is using the full LangChain product suite — including LangChain, LangGraph, and LangSmith — to drive enterprise automation for the cloud.

LinkedIn, Uber, Replit, and Elastic are just a few of the companies using LangGraph for real use cases in production. Learn how they did it below!

Join us this May at Interrupt, LangChain’s inaugural conference where the future of AI agents takes center stage.

Have you ever wanted to take advantage of LangGraph's core features like human-in-the-loop, persistence/memory, and streaming without having to explicitly define a graph? We're excited to announce the release of the Functional API for LangGraph, available in Python and JavaScript. The functional API allows you

By Krish Maniar and William Fu-Hinthorn If you are interested in beta-testing more prompt optimization techniques, fill out interest form here. When we write prompts, we attempt to communicate our intent for LLMs to apply on messy data, but it's hard to effectively communicate every nuance in one

Introducing a new way to run evals using LangSmith’s Pytest and Vitest/Jest integrations.

Captide’s platform transforms how investment research teams work with financial data. By automating the extraction of insights and metrics from regulatory filings and investor relations documents, analysts can create customized datasets and analyses with extreme efficiency. At the heart of this innovation is their commitment to NLP workflows