LangSmith, by LangChain is a framework-agnostic Agent Engineering Platform designed for the observation, evaluation, and deployment of Large Language Model … LangSmith, by LangChain is a framework-agnostic Agent Engineering Platform designed for the observation, evaluation, and deployment of …
automation platforms like Zapier and Make, and AI frameworks including LangChain and Hugging Face to provide unstructured data to Large Language Models … SpecificationsSupported Languages: JavaScript, PythonSupported Frameworks: LangChain, Hugging Face, Puppeteer, PlaywrightCompliance: SOC 2 …
Technical SpecificationsFramework Compatibility: Deep integration with LangChain; framework-agnostic core logic.Implementation: Available in Python and
Flutter, and Kubernetes.AI and cloud platforms: OpenAI, Claude, Gemini, LangChain, Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and modern data
frameworks, including OpenAI, Anthropic, Google Gemini, Amazon Bedrock, LangChain, Pydantic AI, and Vercel AI SDK.Platform integration: Uses Datadog tracing
context retrieval for agent frameworks and tools including Claude, Cursor, LangChain, CrewAI, Agent Development Kit, Cortex, and Genie. Audience & Use CasesDataHub
environments. Its AI engineering work includes frameworks and tools such as LangChain, LangGraph, LlamaIndex, PyTorch, TensorFlow, MLflow, Kubeflow, Docker,
language and keyword query typesIntegrating with third-party tooling such as LangChain to help build sophisticated data pipelines and generative AI applications
applications, databases, and APIs.AI and Agentic Orchestration: Native LangChain integration enables the construction of autonomous AI Agents within workflows
Built-in MCP (Model Context Protocol) server for direct AI agent integration- LangChain integration for RAG and GraphRAG pipelines- TimeSeries model for IoT and
including Claude, ChatGPT, Cursor, VS Code, OpenAI Agents SDK, CrewAI, LangChain, AutoGen, and other MCP-compatible platforms. Business Value Organizations
generation (RAG) workflows. Integrations with development frameworks such as LangChain and LlamaIndex support applications that retrieve contextual records before