How Rakuten AI for Business AI Builds Production-Ready Agents with LangGraph

AI Platform & Solutions - Rakuten is building AI products to empower employees and customers, including Rakuten AI for Business to support business clients in essential operations [1] - Rakuten has built an internal generative AI platform designed for over 70+ businesses across Japan and beyond [1] - Rakuten's agentic workflows are powered by LangGraph, enabling employees to create and share AI agents with minimal coding, aiming to democratize AI [2] Challenges & Solutions - Before using LangGraph and LangSmith, Rakuten struggled with evaluating new models and tools, as well as implementing and testing new agent architectures [2] - LangSmith provided a structured way to test new approaches, improving decision-making beyond intuition, including pairwise A/B testing and accuracy analysis (e.g., from 70% to 80%) [3] Benefits of LangGraph & LangSmith - LangGraph provides an intuitive debugging experience, saving engineering time and becoming the go-to for building production-ready agents [4] - LangGraph helps avoid vendor lock-in by easily swapping models and keeping everything in one ecosystem across teams, improving coordination [4] - Using LangChain's tools, Rakuten has achieved faster time to market, iterating and releasing new AI features faster than competitors [4][5] - Reusable evaluation templates, faster debugging, and easier deployment flows have enabled the engineering team to test and deliver more features [5] Strategic Vision - Rakuten views LangGraph, LangSmith, and the LangChain ecosystem as a foundation for innovation, allowing them to move faster and stay flexible in a fast-changing landscape [6]