n8n for AI development: Automating workflows with Artificial Intelligence

In the modern world, speed and efficiency are key success factors. Routine tasks can take hours that could be spent on more significant things. What if you could automate these processes, especially those involving the use of artificial intelligence, in minutes?

The n8n platform offers a powerful solution for this. By connecting over 420 different services using intuitive visual workflows, n8n becomes an indispensable tool for teams involved in developing and implementing AI solutions, as well as for businesses looking to integrate AI into their operations.

This article is intended for DevOps specialists who seek to understand the technical capabilities and features of n8n in the context of AI, as well as for business leaders and owners evaluating the platform as a foundation for their future AI projects.

What is n8n?

n8n is a flexible low-code automation platform that allows users to create complex chains of actions (workflows) between various applications and services without writing extensive code. Its key advantage is the ability for both self-hosting and using a cloud version, offering flexibility in terms of data and infrastructure control. The platform has both free and paid licenses, targeting different scales of tasks and workloads.

Unlike some alternatives, such as make.com or zapier.com, which offer exclusively cloud-based solutions, n8n provides the possibility of full control over your environment and data, which is critically important when working with sensitive information, including the diverse range of AI applications.

• Low-code Interface: Allows visually assembling complex workflows. This significantly speeds up the prototyping and development of automations, making them accessible not only to developers but also to analysts or data engineers. For technical specialists, this means rapid implementation of typical connections and the ability to focus on unique business logic.
• Deployment options (Self-hosted & Cloud): Choice between your own deployment and a managed cloud. The Self-hosted option is critical for projects where data sovereignty, performance, or specific infrastructure requirements are a priority. Cloud offers convenience and freedom from server management concerns. This choice directly impacts security and regulatory compliance when working with data for AI.
• Over 420+ built-in Integrations: An extensive library of ready-made nodes for popular services (GitHub, Slack, Google Sheets, Google Drive, Telegram, Airtable, databases, cloud storage, etc.). For AI, this means the ability to easily connect the results of model operations to existing business processes, monitoring systems, or communication channels.
• AI Agent Integration: n8n supports the integration of AI Agents that can interact with any Large Language Models (LLM) via API. You can extend the capabilities of agents by giving them access to custom tools, knowledge bases, or other data, making them more autonomous and capable of solving complex tasks. The platform actively uses frameworks like Langchain under the hood to organize these interactions. You can connect all popular providers like OpenAi, Claude (Anthropic), Azure OpenAI, DeepSeek, Google Gemini, Grok, Ollama, Mistral, OpenRouter, as well as use self-hosted models.
• Custom node support & Code node: The ability to create your own nodes in JavaScript and insert code snippets in JavaScript or Python (beta) directly into the workflow using the "Code" node. This provides unlimited flexibility: you can call specific AI services via API, perform complex data pre- or post-processing, implement unique routing logic or interaction with LLMs that is not covered by standard nodes.
• Native API & Webhook handling: Allows building API endpoints and listening for incoming webhooks with minimal effort. Ideal for creating event-driven architectures where an AI workflow is triggered in response to an external event (e.g., new file upload, a trigger in another system, incoming message). Relevant for DevOps when integrating with CI/CD, monitoring systems, or log processing.
• Chat / Form trigger: Allows for quickly testing workflows.
• Workflow versioning & execution logs: Full control over workflow versions and detailed execution logs. This is indispensable for debugging, monitoring performance, identifying errors, and ensuring the reliability of automations in production. Allows analyzing each execution step, which is critical when working with complex AI pipelines.
• Data privacy & ownership: In self-hosted mode, you have full control over your data. This removes many limitations and risks associated with using third-party cloud services, especially when working with confidential data that is processed or generated by AI.
• Rapidly evolving product: The platform is developing very fast.
• Community templates: Website with community-created templates.
• Easy export/import: Workflows can be easily exported and imported.

Let's take a look at the main differences:

Cloud

Pros:

• Almost instant start. No need to own or maintain your infrastructure.

• Global Variables (Pro, Enterprise)

• Shared projects 1/3/unlimited (Starter/Pro/Enterprise)

• Workflow history: 1/5/365 days (Starter/Pro/Enterprise)

• Admin roles (Pro/Enterprise)

• Execution search (Pro/Enterprise)

• SSO (Enterprise)

• Different environments (Enterprise)

• External secret store integration (Enterprise)

• Log streaming (Enterprise)

• Version control using Git (Enterprise)

• Scaling options (Enterprise)

• Extended data retention (Enterprise)

• One-click updates.

Cons:

• Paid tiers only (starts from €20/month). Licenses: Starter/Pro/Enterprise.

• All data and access keys to external services are stored on n8n's servers.

• Does not support community nodes.

Self-Hosted (Free)

Pros:

• All data is stored locally (credentials for all external services, API tokens).

• All user data is controlled by you and does not leave the server without your knowledge.

• Supports community nodes.

• Only one Admin user.

• Users cannot share or see workflows of other users.

Cons:

• Requires a server for hosting n8n.

• Needs regular updates. Updates are released quite often. No LTS branch.

• Requires database backups or at least exporting workflows and credentials.

• Some functionality is unavailable (e.g., Global Variables, Shared projects, Different environments, External secret store integration, Log streaming, Version control using Git, Scaling options, Extended data retention).

• Does not support high load (hundreds of workflow executions per second).

• Some integrations, triggers, and webhooks require a Public IP address.

• Workflow versions history: 1 day.

Self-Hosted (Paid)

Pros:

• Same as Self-Hosted (Free) plus:

• Global Variables

• Unlimited Shared projects

• Extended Workflow history (365 days)

• Admin roles

• Execution search

• SSO

• Different environments

• External secret store integration

• Log streaming

• Version control using Git

• Scaling options

• Extended data retention

• Can set up HA (High Availability).

Cons:

• Same as Self-Hosted (Free) plus:

• Supports Enterprise license only.

If you need to launch a project yesterday, the following might be suitable:

• Cloud solution with a trial period.

• Self-hosted free, if you already have the infrastructure and technical specialists to deploy n8n.

n8n proves to be a highly suitable platform for automating AI-related tasks, especially where AI is part of a broader process.

• Integration with LLM and tools: As mentioned, n8n allows connecting any LLMs available via API (OpenAI, Anthropic, OpenRouter, etc.). You can feed data into the model, process its responses, and use them in the subsequent workflow (e.g., for classification, information extraction, content generation, or decision-making). Integrating knowledge bases (vector databases, traditional DBs) and custom tools (calling external APIs, executing code) allows creating smarter agents capable of acting autonomously within a given scenario.

• Automation based on Langchain: The platform uses frameworks for working with LLMs, such as Langchain, under the hood. This makes n8n a convenient environment for building simple to moderately complex automations based on the concepts of chains and agents. For example, you can automate the process of handling customer requests, where AI classifies the request, extracts key information, initiates action through another service (CRM, tech support), and sends a response back to the user.

• Creating AI bots: n8n is an excellent foundation for creating AI bots that interact with users via messengers (Telegram, Slack), email, or web interfaces, e.g., via Webhook. The workflow can receive an incoming message, pass it to an LLM for analysis and response generation, and then send the response back to the user, potentially after performing some actions (information lookup, status update).

• Recent technical innovations: The ability to create your own MCP (Message Control Protocol) servers, connectable from the client via SSE (Server-Sent Events), opens up prospects for implementing more complex real-time interaction scenarios, which can be useful in some AI applications (e.g., streaming responses from LLMs).

• MCP client: In the N8N AI agent, you can connect third-party MCPs. Their number is constantly growing.

• Custom logic in Node.js and Python: If the standard AI or Agent nodes do not provide the necessary functionality, or if specific data processing logic is required (e.g., working with embeddings, calling a custom model, complex text post-processing), it can be implemented using the Code or Custom Node (Node.js only) nodes. This provides the necessary flexibility for integrating with highly specialized AI services or models.

n8n, like any platform, has its strengths and aspects that require attention, especially in production environments and when dealing with complex AI tasks.

• Development speed vs. complexity: The platform allows automating relatively simple logic very quickly. The visual interface speeds up assembly and testing. However, when attempting to implement overly complex logic in a single workflow, the process can become cumbersome and difficult to manage. We strongly recommend against creating monolithic, extremely complex workflows, especially for critical AI processes. It is better to break down tasks into several smaller, specialized workflows that interact with each other.

• Debugging: Debugging in n8n is generally quite convenient thanks to step-by-step execution logs. However, when working with AI nodes or custom code where errors occur in internal calls (e.g., to an LLM API or a custom function), detailed error information from "under the hood" of the node can sometimes be unavailable directly in the n8n UI. This may require additional logging within the custom code or checking the logs of the LLM service itself. We have accumulated experience in diagnosing and solving such issues.

• Platform Evolution: n8n is developing rapidly, with new versions released quite often. This brings new features and improvements but also means that there is no stable LTS (Long-Term Support) branch. For production systems, this requires a thoughtful approach to updates and testing to ensure compatibility and stability.

• Performance and scaling: For handling heavy loads and ensuring high availability, a paid version is typically required with corresponding scaling and support capabilities. The self-hosted deployment architecture must also consider resource requirements (CPU, RAM, network) depending on the expected load, especially when working with heavy models or large volumes of data.

• Using custom Node/Code: The ability to write your own logic in Node.js and Python is a huge advantage. However, it requires relevant expertise from the team. Well-written and thoroughly tested custom nodes and code snippets are critical for the stability of the entire workflow.

• Credentials: Access keys to external services are stored in the Credentials section in encrypted form and can be used across different workflows.

• Error handling: Use the Error workflow in workflow settings to handle errors gracefully.

• Timeouts: Use Workflow timeout execution settings (global or workflow level) to prevent workflows from running indefinitely.

n8n is a powerful and flexible tool for integrating and automating AI solutions. It is excellently suited for:

• Rapid prototyping and integration of AI into existing processes.

• Creating automated data processing pipelines using AI.

• Developing AI bots and agents that interact with users and systems.

• Integrating AI functionality into current processes (e.g., automatic response to social media feedback).

• Projects where control over data is critical (self-hosted).

By choosing n8n, you get a platform that combines the speed of low-code development with the flexibility of full coding where necessary. It allows teams to quickly respond to business needs and integrate innovative AI capabilities without needing to build the entire integration infrastructure from scratch.

We, as a team with experience working with n8n and a deep understanding of AI technologies, are ready to help you unlock the full potential of this platform. We know how to build scalable and reliable solutions, effectively use the capabilities of custom code and nodes, and navigate the nuances of debugging complex workflows, including those related to AI.

If you are looking for a way to accelerate the implementation of AI in your business processes or optimize existing workflows with artificial intelligence, n8n in our hands can be the key to achieving your goals.

• Instant and personalized response to feedback/complaint messages. With the help of AI, you can determine the category of a message and send a notification to the responsible manager for messages requiring a quick reaction.

• SMM Assistant

1. Content preparation for social media, website. Searching for information online based on given keywords, generating publication text considering the specifics of each social network.

2. Image generation for publications.

3. Video generation.

4. Translation of videos, publications into other languages.

5. AI Chatbots.

n8n is a practical choice for teams looking to automate and scale AI-driven processes without starting from scratch. It blends the speed of low-code interfaces with the flexibility of full-code customization, making it ideal for rapid prototyping, intelligent data handling, and building interactive AI agents. With self-hosted deployment, you retain full control over data, a key factor in enterprise environments. And with UKAD’s experience in n8n and AI adoption, we help you move from concept to a fully functioning system quickly and reliably. Whether you aim to build smarter workflows, enhance user interactions, or streamline operations with AI, we’re ready to make it work.