--- title: Langchain Reviews meta_title: 'Langchain Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 108 reviews by the users' company size, role or industry to find out how Langchain works for a business like yours. aggregate_rating: rating_value: 4.5 review_count: 108 scale: '5' date_modified: '2026-08-15' parent_category: name: Generative AI url: https://www.g2.com/categories/generative-ai --- # Langchain Reviews **Vendor:** Langchain **Category:** [Generative AI Infrastructure Software](https://www.g2.com/categories/generative-ai-infrastructure) **Average Rating:** 4.5/5.0 **Total Reviews:** 108 ## About Langchain LangChain is an open-source framework designed to simplify the development of applications powered by large language models (LLMs). By providing a suite of tools and abstractions, LangChain enables developers to build context-aware, reasoning applications such as chatbots, question-answering systems, and content generators. Its modular architecture allows for seamless integration with various LLMs, including those from OpenAI, Anthropic, and Cohere, facilitating the creation of sophisticated AI-driven solutions. Key Features and Functionality: - Modular Components: LangChain offers isolated modules for model input/output, prompt templates, and retrieval mechanisms, allowing developers to customize and extend functionalities as needed. - Agent Framework: The framework supports the creation of agents that can make decisions and perform tasks based on user inputs, enhancing the interactivity and utility of applications. - Memory Management: LangChain provides both short-term and long-term memory capabilities, enabling applications to maintain context over extended interactions. - Extensive Integrations: With over 1,000 integrations, LangChain allows developers to connect with various models, tools, and databases without the need to rewrite application code, ensuring flexibility and future-proofing. - Durable Runtime: Built on LangGraph’s durable runtime, LangChain ensures agents have built-in persistence, rewind capabilities, checkpointing, and support for human-in-the-loop interactions. Primary Value and Problem Solving: LangChain addresses the challenges developers face when integrating LLMs into applications by offering a structured and efficient approach to building AI-driven solutions. It streamlines the development process, reduces the complexity associated with managing interactions between various components, and provides the flexibility to adapt to evolving AI technologies. By leveraging LangChain, developers can rapidly deploy reliable and scalable AI applications that are capable of understanding and responding to complex user inputs, thereby enhancing user experiences and operational efficiency. ## Langchain Pros & Cons **What users like:** - Users find Langchain's **ease of use** invaluable for quickly building complex AI applications with various integrations. (15 reviews) - Users appreciate the **easy integrations** of Langchain, enabling seamless connections between LLMs and various APIs. (14 reviews) - Users appreciate the **user-friendly features** of Langchain, making powerful capabilities accessible to those with basic AI knowledge. (10 reviews) - Users admire the **seamless integrations** of LangChain, which enhance efficiency in developing AI applications and workflows. (7 reviews) - Users appreciate the **customization capabilities** of LangChain, enabling tailored AI solutions while simplifying app development. (5 reviews) - Community Support (4 reviews) - Users praise the **excellent documentation** and community support of Langchain, enhancing the development experience for LLM applications. (4 reviews) - Flexibility (4 reviews) - Scalability (4 reviews) - Chatbot Creation (3 reviews) **What users dislike:** - Users find **complexity issues** with Langchain, citing heavy abstractions and a steep learning curve that hinder productivity. (9 reviews) - Users find Langchain's **steep learning curve** overwhelming, requiring deep knowledge of its components and frequent API changes. (9 reviews) - Users find the **poor documentation** of LangChain confusing and outdated, complicating their development process. (7 reviews) - Users struggle with **software instability** due to frequent breaking changes that complicate long-term project maintenance. (4 reviews) - Users find **error handling challenging** in Langchain, complicating debugging and increasing frustration with nested components. (3 reviews) - Users experience **slow performance** with Langchain, noting delays and the need for better optimisation and faster alternatives. (3 reviews) - API Limitations (2 reviews) - Limited Access (2 reviews) - Model Issues (2 reviews) - Users note that Langchain can be **expensive** due to reliance on many additional packages, increasing overall costs. (1 reviews) ## Langchain Reviews ### 1. Langchain Review **Rating:** 5.0/5.0 stars **Reviewed by:** Akshet P. | NA, Enterprise (> 1000 emp.) **Reviewed Date:** April 09, 2025 **What do you like best about Langchain?** The framework is really good, and building an RAG pipeline is very easy and robust; part from that, making complex and advanced RAG pipelines is simple enough while being scalable at the same time. **What do you dislike about Langchain?** Due to changes in the functions, some functions are deprecated that chatGPT is yet to identify, so it sometimes adds time to go through the documentation. **What problems is Langchain solving and how is that benefiting you?** helps building RAG pipleines easy havinh open sources models to use also gives a very easy intefgraito of paid mdels using API keys. Framwork is well made and the community is really good, growing and helpful. ### 2. Benefits of Langchain **Rating:** 4.0/5.0 stars **Reviewed by:** Deepak Y. | AI Research Associate Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 08, 2025 **What do you like best about Langchain?** Langchain is best for building and handling the RAG based application. **What do you dislike about Langchain?** Resource are very easily available and very user friendly interface **What problems is Langchain solving and how is that benefiting you?** Langchain is used to train the RAG based application and useful for LLM Model. ### 3. Langchain review for AI and agentic usecase **Rating:** 5.0/5.0 stars **Reviewed by:** Debishree T. | Software Consultant, Small-Business (50 or fewer emp.) **Reviewed Date:** July 27, 2025 **What do you like best about Langchain?** The knowledge graph feature for visualisation **What do you dislike about Langchain?** Heavy datasets take longer on local development **What problems is Langchain solving and how is that benefiting you?** Agentic AI usecase with knowledge grapg ### 4. Use full capabilities of GenAI without a hassel **Rating:** 5.0/5.0 stars **Reviewed by:** Subham A. | Sr. Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 07, 2025 **What do you like best about Langchain?** I use langchain.js , and I like its composability and availablilty of different readers or database drivers with it **What do you dislike about Langchain?** I have nothing to dislike about it, Langchain is really a great product **What problems is Langchain solving and how is that benefiting you?** most of the time we use langchain for our RAG applications but apart from this we have Integrated many AI based workflows as well which acyually calls multiple chains and workflows based on conditions ### 5. Brief review of LangChain **Rating:** 4.5/5.0 stars **Reviewed by:** Dwaipayan B. | Associate Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** November 09, 2024 **What do you like best about Langchain?** It is one of the best packages required to use Large Language Models in the field of Generative AI, it is easy to adapt and works like a charm and it keeps upgrading itself to be compatible with the latest technology **What do you dislike about Langchain?** Sometimes some feature might not be present in the latest version of langchain which was previously there, so we have to rewrite our code to match with the new version, if they could just support the older versions as well then it would have been better. **What problems is Langchain solving and how is that benefiting you?** It is the primary package I use to develop Generative AI based applications, it does everything related to that field so it solves most of the problems faced in the field of LLMs and Generative AI. ### 6. Langchain - LLM + RAG + TOOLS **Rating:** 5.0/5.0 stars **Reviewed by:** shiv a. | AI / NLP Engineer, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** April 11, 2024 **What do you like best about Langchain?** now I can Connect Any number of LLMs with any Number of Tools. I am making Agents using Multiple Prompts. I can create and add memories to my conversational chain. I can read from PDFs as well as databases with different vector databases. I can also integrate LLMs like OpenAI, Mistral, Llama, etc with the Internet as well as with APIs It gets Additional Data. It's Easy to Use and Implement in code. **What do you dislike about Langchain?** I feel like the code written in Python for Langchain makes it a little slower. Also, there are restrictions in using OpenAI or Claude Function calling with langchain. Also, there are better faster solutions like Haystack. **What problems is Langchain solving and how is that benefiting you?** Langchain integrates APIs, Tools, InMemoryCache, and supports multiple Agents, Multiple LLMS, Multiple VectorDBs, Multiple conversations, and retrieval chains. Langchain helps to make AI/ LLM Agents that can Work together in research, in automation as well and in creating solutions using tools that can connect to the internet as well as to databases. We can make our own custom LLM that can work on provided data using open or closed-source LLM's APIs. ### 7. Good framework for handling LLMs **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Automotive | Enterprise (> 1000 emp.) **Reviewed Date:** July 09, 2024 **What do you like best about Langchain?** Easy Handel and productive options for usage made faster execution **What do you dislike about Langchain?** Nothing as of now as we use it didn't face any issues **What problems is Langchain solving and how is that benefiting you?** Legacy way of handling LLM is handled now with langchain ### 8. Powering LLMs **Rating:** 5.0/5.0 stars **Reviewed by:** Adam L. | Founder, CEO (Sold to MetaGoose Technologies Inc), Small-Business (50 or fewer emp.) **Reviewed Date:** October 31, 2023 **What do you like best about Langchain?** Langchain is almost a fundamental for any build I do with AI. It really is the oil that greases the wheel. **What do you dislike about Langchain?** Hard to think of something outside its natural complexity to dislike. **What problems is Langchain solving and how is that benefiting you?** Connecting LLMs together is a key feature in most of our builds. It would be impossible without Langchain ## Langchain Discussions - [How are you handling LangChain and LangGraph breaking changes and debugging in multi-step workflows?](https://www.g2.com/discussions/how-are-you-handling-langchain-and-langgraph-breaking-changes-and-debugging-in-multi-step-workflows) - 1 upvote - [View Langchain pricing details and edition comparison](https://www.g2.com/products/langchain/reviews?page=3§ion=pricing&secure%5Bexpires_at%5D=2026-08-15+08%3A42%3A28+-0500&secure%5Bsession_id%5D=30380058-17a4-408e-93cf-a61d38b7dca5&secure%5Btoken%5D=23527dd8ca56d31c96faeb7ca31bc856438d6ce67877d9755a1723fb14f9461c&format=llm_user) ## Langchain Integrations - [Apache Airflow](https://www.g2.com/products/apache-airflow/reviews) - [AWS Bedrock](https://www.g2.com/products/aws-bedrock/reviews) - [Chroma Vector Database](https://www.g2.com/products/chroma-vector-database/reviews) - [Claude](https://www.g2.com/products/claude-2025-12-11/reviews) - [Claude Code](https://www.g2.com/products/anthropic-claude-code/reviews) - [Google Vertex AI SDK](https://www.g2.com/products/google-vertex-ai-sdk/reviews) - [GroqCloud](https://www.g2.com/products/groqcloud/reviews) - [Hugging Face smolagents](https://www.g2.com/products/hugging-face-smolagents/reviews) - [Jira](https://www.g2.com/products/jira/reviews) - [LangGraph](https://www.g2.com/products/langgraph/reviews) - [LangSmith](https://www.g2.com/products/langsmith/reviews) - [LlamaIndex](https://www.g2.com/products/llamaindex/reviews) - [Microsoft Copilot](https://www.g2.com/products/microsoft-microsoft-copilot/reviews) - [Milvus](https://www.g2.com/products/milvus/reviews) - [Mistral 7B](https://www.g2.com/products/mistral-7b/reviews) - [n8n](https://www.g2.com/products/n8n/reviews) - [Openai](https://www.g2.com/products/openai/reviews) - [OpenAI SDK](https://www.g2.com/products/openai-sdk/reviews) - [Python](https://www.g2.com/products/python/reviews) - [Semantic UI React](https://www.g2.com/products/semantic-ui-react/reviews) - [Visual Studio Code](https://www.g2.com/products/visual-studio-code/reviews) ## Langchain Features **Additional Functionality** - Tagging - Natural Language Processing - Data Extraction - Multi-Language - Predictive Analytics - Drag & Drop - Speech Recognition - Reporting/Analytics - Data Storage Management - Virtual Personal Assistant (VPA) - AI Copilot - Customer Segmentation - Collaboration Tools - Data Import/Export - Generative AI - For eCommerce - Role-Based Permissions - Customizable Branding - Search/Filter - Monitoring - Document Management - API - Data Visualization - Trend Analysis - Machine Learning - Access Controls/Permissions - Alerts/Escalation - Performance Metrics - Real-Time Data - Third-Party Integrations - Mobile App - Multiple Data Sources - For Sales Teams/Organizations - Sentiment Analysis - Activity Dashboard - Chatbot - Workflow Automation **Additional Functionality** - Code Generation - Text to Image - Generative AI - API - Natural Language Processing - Virtual Characters and Avatars - Content Generation - Personalization and Recommendation - Conditional Generation - Transformer Model - Automated Image & Video Editing - Interactive and Co-Creative Systems - Text Summarization - Data Augmentation - Variation Autoencoder Models - Adversarial Training - Transfer Learning and Fine-tuning - Simulation and Scenario Generation - Creative Design - AI Copilot - Prompt Engineering - Foundation Model **Scalability and Performance - Generative AI Infrastructure** - AI High Availability - AI Model Training Scalability - AI Inference Speed **Prompt Engineering - Large Language Model Operationalization (LLMOps) ** - Prompt Optimization Tools - Template Library **Inference Optimization - Large Language Model Operationalization (LLMOps)** - Batch Processing Support **Customization - AI Agent Builders** - Natural Language Configuration - Tone Customization - Security Guardrails - API Security - Data Security - Authentication **Prompt Management - Prompt Management Tools** - Prompt Chaining and Orchestration - Change tracking - Prompt Behaviour Feedback **Workflow Design & Integration - AI Orchestration** - Dependency Management - Workflow Coordination - Multi-Provider API Connectivity - Multi-Step Workflow Creation - Enterprise System Integration - Real-Time Data Pipelines **Cost and Efficiency - Generative AI Infrastructure** - AI Cost per API Call - AI Resource Allocation Flexibility - AI Energy Efficiency **Model Garden - Large Language Model Operationalization (LLMOps)** - Model Comparison Dashboard **Functionality - AI Agent Builders** - Omni-channel Support - Agent Branding - Proactive Response Capabilities - Seamless Human Escalation - Multimedia Support - Multi-Modal Input Support **Performance Analytics - Prompt Management Tools** - Lower Latency - Token Usage - Cost Control **Performance Optimization & Analytics - AI Orchestration** - Workflow Performance Dashboards - Workflow Reporting - Resource Utilization Monitoring - Computational Resource Management - Dynamic Scaling - Component Monitoring **Integration and Extensibility - Generative AI Infrastructure** - AI Multi-cloud Support - AI Data Pipeline Integration - AI API Support and Flexibility **Custom Training - Large Language Model Operationalization (LLMOps)** - Fine-Tuning Interface **Data and Analytics - AI Agent Builders** - Analytics & Reporting - Contextual Awareness - Data Privacy Compliance **Model Benchmarking and Comparison - Prompt Management Tools** - Strategic Model Selection **Governance & Compliance Controls - AI Orchestration** - Regulatory Compliance - Governance Policy Enforcement - Role-Based Access Control - Audit Trail Management - Security Protocols **Security and Compliance - Generative AI Infrastructure** - AI GDPR and Regulatory Compliance - AI Role-based Access Control - AI Data Encryption **Application Development - Large Language Model Operationalization (LLMOps) ** - SDK & API Integrations **Integration - AI Agent Builders** - Workflow Automation - API Usage - Platform Interoperability - CRM Data Integration - Third-Party Integrations **Production-ready Deployment Tools - Prompt Management Tools** - CI/CD Integration **Additional Functionality** - Version Control - Scalability - Personalization - Data Extraction - Webhooks - API - Natural Language Processing - Fallback Handling - Drag & Drop - Multiple LLM Models - Built-in AI Assistant - Automated Testing - Data Governance - Collaboration Tools - Pre-built Templates - Agent Design Tools - Deep Learning - Model Training - Analytics - Single Sign On - Debugging - Deployment Management - Proactive Error Detection **Usability and Support - Generative AI Infrastructure** - AI Documentation Quality - AI Community Activity **Model Deployment - Large Language Model Operationalization (LLMOps) ** - One-Click Deployment - Scalability Management **Prompt Performance - Prompt Management Tools** - Real-time Visibility **Guardrails - Large Language Model Operationalization (LLMOps)** - Content Moderation Rules - Policy Compliance Checker **Model-specific Tuning - Prompt Management Tools** - Model -specific Tuning **Model Monitoring - Large Language Model Operationalization (LLMOps)** - Drift Detection Alerts - Real-Time Performance Metrics **Security - Large Language Model Operationalization (LLMOps)** - Data Encryption Tools - Access Control Management **Gateways & Routers - Large Language Model Operationalization (LLMOps)** - Request Routing Optimization ## Top Langchain Alternatives - [UiPath Agentic Automation](https://www.g2.com/products/uipath-agentic-automation/reviews) - 4.6/5.0 (6,136 reviews) - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (727 reviews) - [Botpress](https://www.g2.com/products/botpress/reviews) - 4.5/5.0 (421 reviews)