Most AI applications fail to scale. Despite a maturing $200B+ AI market, only 5% of custom enterprise AI solutions make it to production. Why? Because the infrastructure isn’t where it needs to be. Models have to connect to data scattered across fragmented systems, workflows need to run reliably over chains of complex steps and outputs require constant oversight. Trying to stitch these elements together so they work consistently is like building a skyscraper with duct tape and scaffolding–it might hold for the demo, but it crumbles in real-world scenarios.
Just as cloud computing created the need for new infrastructure layers, the shift to agentic AI demands purpose-built platforms that can abstract away complexity and enable developers to move from experimentation to production with confidence. We’ve seen this movie before. When new computing paradigms emerge, the companies that provide foundational infrastructure often become the most valuable.
That’s where LangChain comes in. What started as an open-source framework has become one of the most widely adopted platforms for building intelligent agents, powering both global enterprises and AI-native startups. We believe LangChain is positioned to be the platform for agent engineering. For these reasons and more, we are thrilled to back LangChain, participating in the company’s $125M Series B.
From Prototype to Production-Ready: Why Leading Enterprises Run on LangChain
The rise of intelligent agents has raised the bar for infrastructure. Teams now need more than model API calls, they need platforms that can choreograph multi-step workflows, provide visibility into agent-decision making and deliver secure, reliable deployment at scale.
LangChain is an end-to-end solution engineered to tackle rising infrastructure challenges, with each layer solving a critical piece of the agentic puzzle.
- LangChain library forms the foundation, providing the essential building blocks and primitives connecting AI models to data, tools, and reasoning chains across any provider.
- LangGraph serves as a powerful orchestration layer providing memory, human-in-the-loop support, and durable execution for managing complex, multi-step workflows at scale.
- LangSmith ties it all together with a full-stack agent engineering platform, allowing teams to trace agent behavior, continuously test against real production data, and deploy confidently at scale with infrastructure built for enterprise demand.
By unifying these layers, LangChain enables what they call “agent engineering” – turning unpredictable AI systems into reliable, scalable experiences with observability, orchestration, and enterprise reliability baked in.
And while most AI solutions lack durability or lock teams into rigid ecosystems, LangChain stands apart. Open, modular and already embedded at the center of AI-native startups like Clay (a Sapphire portfolio company) and Replit, as well as Fortune 500 enterprises such as LinkedIn and Workday.
The proof of their differentiation lies in how enterprises are deploying it. Klarna powers its AI Assistant for 85 million active users on LangChain, handling complex payment escalations and multi-departmental workflows. Rakuten uses LangChain and LangSmith to build its AI for Business platform across an ecosystem of 70+ businesses. Replit leverages LangGraph and LangSmith to orchestrate workflows and ship AI-native developer tools at a rapid pace. These aren’t just one-off experiments, they are mission-critical systems running on LangChain.
The Architects Behind an Agentic Future
Harrison Chase,
CEO + Co-founder, LangChain
Behind LangChain’s rise is a founding team built for this moment. Co-founder and CEO, Harrison Chase is one of the most trusted voices in the AI developer community, combining technical expertise with a clear understanding of enterprise environments. Before founding LangChain, his experience at Robust Intelligence and at fintech startup Kensho gave him firsthand insight into the challenges of moving AI from prototype to production.
Ankush Gola,
Co-founder, LangChain
Co-founder, Ankush Gola, complements Chase’s experience with deep infrastructure expertise from scaling systems at Facebook and Robust Intelligence, which has proven essential as enterprises deploy LangChain at scale. Together, they’ve created a company that has already become the de facto framework for many developers experimenting with language models and is cementing its role as the platform enterprises depend on as they bring AI into production. We believe this blend of developer trust and infrastructure know-how has fueled LangChain’s emergence as a category-defining platform.
Powering the Next Era of Software
Intelligent agents are poised to become as indispensable as cloud platforms and data warehouses, and LangChain is creating the infrastructure that will make them possible.
At Sapphire Ventures, we aim to partner with companies building the infrastructure in every technological paradigm shift, including category-defining players such as Glean, Moveworks, Auth0, Weights & Biases, Monday.com, DocuSign, Box, LinkedIn and Netskope. As we look to the future of AI, we’re proud to partner with Harrison, Ankush, and the LangChain team as they build the defining platform for agents.
If you’re interested in learning more about LangChain or exploring opportunities to join, you can find more information here.
Sign up for our newsletter
Legal disclaimer
This article is for informational purposes only. Nothing presented within this article is intended to constitute investment advice, and under no circumstances should any information provided herein be used or considered as an offer to sell or a solicitation of an offer to buy an interest in any investment fund managed by Sapphire. Information provided reflects Sapphires’ views as of a time, whereby such views are subject to change at any point and Sapphire shall not be obligated to provide notice of any change. Companies mentioned in this article are a representative sample of portfolio companies in which Sapphire has invested in which the author believes such companies fit the objective criteria stated in commentary, which do not reflect all investments made by Sapphire. A complete alphabetical list of investments made by Sapphire’s Growth strategy is available here. No assumptions should be made that investments listed above were or will be profitable. Due to various risks and uncertainties, actual events, results or the actual experience may differ materially from those reflected or contemplated in these statements. Nothing contained in this article may be relied upon as a guarantee or assurance as to the future success of any particular company. Past performance is not indicative of future results.
