Langflow AI Agent Builder - Managed AMI by cloudimg

This is a repackaged open source software product wherein additional charges apply for cloudimg support services.

Overview

Langflow is the open source, low-code visual builder for AI agents, chatbots, and retrieval augmented generation (RAG) applications with over 50,000 GitHub stars. You design flows by dragging and connecting components on a canvas - language models, prompts, vector stores, retrievers, tools, and agents - then run and serve them through a built-in API. This AMI delivers Langflow fully installed, hardened, and configured as a system service so you have a production-ready AI agent builder running within minutes of launch - no manual setup, no security gaps. The current release is Langflow 1.9.

Why This AMI Instead of a Manual Install

Installing Langflow yourself means writing systemd units, configuring nginx, enabling authentication (disabled by default), generating encryption keys, and separating data from the OS disk. This image handles all of that before you log in for the first time. You skip hours of configuration and avoid the risk of shipping an unauthenticated AI builder to production.

Application Stack

Langflow is installed into a dedicated Python3.12 virtual environment under /opt/langflow and run by an unprivileged service account. It listens on the loopback address while an nginx reverse proxy fronts the application on port 80, with WebSocket and streaming upgrade headers for real-time flow output and a raised upload limit for file ingestion. A systemd service starts Langflow on boot and restarts it on failure.

Secure by Default

Langflow ships with authentication disabled out of the box. This image requires login from the start: it creates a single administrator account whose password, and the key used to encrypt credentials stored in your flows, are generated uniquely for your instance on first boot and written to a root-only file. No shared or default credentials ship in the image.

Ready to Use

Browse to the instance on port 80, sign in as the administrator, and start building. Connect Langflow to any language model endpoint - OpenAI, Anthropic, Amazon Bedrock, or a self-hosted model - and to your vector store of choice. Your flows, database, and encryption key live on a dedicated, independently resizable storage volume kept separate from the operating system disk. Because Langflow calls out to an external model endpoint, the image is CPU-only and ships no model weights.

Use Cases

• Healthcare and life sciences teams building internal Q&A agents that ingest clinical or research documents into a vector store and serve answers to staff without sending data to a third-party SaaS platform.
• Financial services and legal teams with data residency or regulatory requirements (GDPR, FCA, HIPAA) who need a self-hosted, in-VPC alternative to SaaS agent builders.
• Engineering teams prototyping and deploying retrieval augmented generation pipelines, connecting internal knowledge bases to LLMs, and serving the result through Langflow's built-in API.
• Operations teams automating internal workflows - ticket triage, document summarization, customer support drafts - with visual agent flows rather than custom code.

cloudimg Support

24/7 technical support by email and live chat. Our engineers help with Langflow deployment, connecting language model and vector store providers, building agent and RAG flows, serving flows through the API, TLS termination, and scaling. Critical issues receive a one-hour average response.

Get Started

Launch the AMI, retrieve your unique admin credentials from the root-only file, and sign in. To discuss your use case or get a guided walkthrough of your first flow, contact our team at support@cloudimg.co.uk .

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