n8n

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n8n

n8n is a fair-code workflow automation platform designed for "agentic workflows." It features a visual node editor and supports custom code, offering over 400 integrations to connect various applications and services. This platform enables users to automate complex tasks and build sophisticated workflows with ease, making it a powerful tool for developers and automators alike.

General
Author	n8n GmbH
Release Date	2019
Website	https://n8n.io/
Documentation	https://docs.n8n.io/
Technology Type	Workflow automation platform

Key Features

Visual Workflow Editor: Drag-and-drop interface for building complex workflows without writing extensive code.
400+ Integrations: Connects with a vast array of applications, databases, and APIs.
Custom Code Support: Allows for JavaScript/TypeScript functions within workflows for advanced customization.
Fair-Code Licensing: Provides transparency and community contributions while maintaining commercial viability.
Agentic Workflows: Designed to facilitate advanced automation scenarios often found in AI-driven applications.
Data Transformation: Tools for manipulating and transforming data between different steps in a workflow.

Start Building with n8n

n8n offers powerful capabilities for automating tasks and integrating systems. Its visual editor and extensive integrations make it accessible for rapidly building "agentic workflows." Developers can leverage n8n to connect AI models, manage data flows, and automate responses across various platforms. Explore the official documentation and community examples to see how n8n can enhance your projects.

👉 Start building with n8n 👉 n8n Integrations

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n8n AI Technologies Hackathon projects

Discover innovative solutions crafted with n8n AI Technologies, developed by our community members during our engaging hackathons.

APIlot: Intelligent API Navigator

Anyone who spends their days deep in API integration knows the pain of losing countless hours simply trying to parse documentation. Figuring out which endpoints actually exist, what fields are strictly required versus optional, and what exact data types to pass is a tedious, manual bottleneck that slows down development. I built APIlot to completely eliminate this friction. APIlot is an AI-powered API navigator that transforms static, overwhelming documentation into a clean, interactive workspace. You simply drop an API documentation URL into the app. From there, APIlot intelligently reads the docs, extracts every single endpoint, and dynamically generates an interactive form showing you exactly what fields you need to fill to build your payload. No more endless scrolling or command-F searching. Built for the AMD Developer Hackathon, APIlot relies on a robust, cloud-based architecture so no local GPU is required: • Intelligent document scraping is handled via Firecrawl. • The heavy lifting of schema extraction and LLM inference runs on AMD Developer Cloud (MI300X) instances. • Model serving is managed via Ollama on AMD Developer Cloud instances, securely exposed via Cloudflared • Agentic workflow orchestration is driven by n8n. • The frontend is a snappy React + Vite interface featuring a live, syntax-highlighted payload terminal. APIlot's goal is simple: let integrators read less, so they can build more.

Neural Market

The traditional financial system was built for humans, but the next evolution of the internet belongs to autonomous agents. NeuralMarket is a high-speed, fully autonomous task marketplace designed from the ground up for the emerging Machine-to-Machine (M2M) economy. In NeuralMarket, human intervention is obsolete; AI agents independently evaluate tasks, negotiate pricing, execute workflows, and settle payments in real-time. To make this possible, we required a financial layer that could operate at the speed of code. We integrated Circle Programmable Wallets to programmatically generate and assign secure wallets to individual AI workers on the fly. Because our platform relies on an advanced, Python-based AI Economic Forecaster that dynamically calculates market demand, task complexity, and baseline pricing, price stability is absolutely paramount. Therefore, USDC is the exclusive settlement layer of NeuralMarket, ensuring our agents' micro-bidding models (e.g., 0.0015 USDC) are never corrupted by asset volatility. Powered by a robust FastAPI backend and a seamless Cloudflare Pages frontend, NeuralMarket abstracts away the complexities of blockchain gas fees. We have built the foundational infrastructure for the "Agentic Economy"—a future where AI models don't just generate code, but actively participate in global financial markets.

n8n × x402 Paywall

n8n-nodes-x402-paywall Turn any n8n workflow into a pay-per-call USDC endpoint. A production-quality n8n community node that drops an x402 paywall in front of any workflow. Clients get a 402 Payment Required, sign an EIP-3009 USDC authorization, and on settlement the node triggers the workflow and returns its result. Settlement runs onchain on Arc testnet via a self-hosted x402 facilitator. Built for the Agentic Economy on Arc — Nano-Payments hackathon (LabLab x Circle x Arc, April 2026). What's included: - X402 Paywall trigger node: owns the webhook, issues 402s, verifies and settles payments, then fires the workflow with payment metadata attached. - Self-hosted x402 facilitator for Arc testnet (Express + @x402/core + @x402/evm), since the public facilitator doesn't yet support Arc. - Burst client that signs and submits 50+ real paid requests to prove per-action economics. Live demo: deployed behind Caddy TLS on our VPS inside n8n 2.17.6. Unpaid: curl -k -i https://2.26.21.34/webhook/x402-demo Signed: pnpm burst -- --count 1 --url https://2.26.21.34/webhook/x402-demo First settlement onchain: https://testnet.arcscan.app/tx/0xc67c4fe4baac112e3ea03b4166539e08d1fa8911d7ba1ea4d4257d850adb168a Install: npm install n8n-nodes-x402-paywall Restart n8n — the X402 Paywall trigger appears in the node picker. Key config: HTTP method, path, price in USD (hackathon cap 0.01), network (arcTestnet), timeout, response mode. Credentials require a Pay-To EVM address and facilitator URL. Hackathon: Agentic Economy on Arc — Nano-Payments (LabLab x Circle x Arc, April 2026). Track: Best Autonomous Commerce Application. Team: Nikolay Micheev + Vadim Buss. Per-action price: 0.001 USDC. Evidence: 50+ settled transactions on Arc testnet, verified on Arcscan. Original work built for this hackathon — not a fork. External deps: @x402/core and @x402/evm (Apache-2.0). License: MIT

JaaS — Jurisprudence-as-a-Service

JaaS (Jurisprudence-as-a-Service) is an autonomous legal intelligence engine that transforms how jurisprudential knowledge is consumed, computed, and monetized—entirely machine-to-machine. THE PROBLEM: Traditional legal research is slow, expensive, and locked behind rigid SaaS subscriptions that cannot serve the emerging agentic economy. When AI agents need specialized legal knowledge on demand, they face two barriers: (1) no programmatic access to curated jurisprudence, and (2) gas costs on Ethereum L1 ($2.00+) that make micro-transactions economically impossible. THE SOLUTION: JaaS deploys a multi-agent orchestration architecture where Gemini 3 Pro acts as the reasoning engine, routing complex queries through specialized extraction models (Featherless Qwen2.5-3B) via the x402 HTTP Payment Protocol. Every query is settled in USDC on the Arc blockchain for fractions of a cent, enabling a true pay-per-compute model with zero subscriptions and zero counterparty risk. TECHNICAL ARCHITECTURE: - Orchestrator Agent (Gemini 3 Pro): Parses legal queries, establishes reasoning paths, and synthesizes final jurisprudential reports. - Extractor Agent (Featherless Qwen2.5-3B): Performs low-level doctrine extraction and citation mapping via isolated API calls. - Payment Layer (Circle DCW + x402 + Arc): Every agent computation triggers an HTTP 402 nanopayment, settled on-chain via Circle Developer-Controlled Wallets on the Arc Testnet. UNIT ECONOMICS (Validated): - Revenue per query: $0.01 USDC - AI inference cost: $0.0020 USDC - Arc network gas: $0.00002 USDC - Gross margin: 79.8% - On Ethereum L1, the same operation yields -5,000% margin. STRESS TEST: We executed 50+ sequential on-chain legal queries with a 100% success rate, zero failures, and sub-second USDC settlement on every transaction—proving Arc's viability for high-frequency agentic workloads.

Rydlr Motion Studio (Movimento)

Rydlr Motion Studio (Movimento) is a trust-less motion-commerce platform for AI-generated character animation. We turn every blend, validation, and runtime usage event into an economically viable transaction so creators can monetize motion assets at internet scale, not through slow licensing cycles. Our system uses Gemini for multimodal motion understanding and reasoning, then applies an oracle-based novelty pipeline to score whether a generated blend is meaningfully new. If approved, the motion pack is attested and registered on Arc, where settlement is handled in USDC with predictable, sub-cent costs. The core innovation is per-action pricing with real-time settlement: developers can charge per blend request, per animation second, or per downstream usage event, and route revenue instantly to creator, platform, and service participants. This makes high-frequency micro-commerce practical for AI and game workflows where traditional gas economics would destroy margin. Instead of batching or off-chain trust assumptions, transactions can be settled continuously with deterministic finality and clean auditability. Movimento is designed for the Agentic Economy: autonomous systems can request motion generation, pay for analysis, receive attestations, and trigger follow-on usage billing without manual reconciliation. In our demo flow, users submit motion inputs, receive an AI-generated explanation of style transitions, get a novelty decision, and then execute on-chain authorisation and usage settlement in one continuous loop. We also provide transparent economic reporting that shows why this model is viable on Arc for <$0.01 actions and why it is not viable under traditional gas-heavy networks. The result is a production-oriented foundation for machine-to-machine creative commerce powered by Gemini intelligence and Arc-native USDC settlement.

Kraken Trading Agent

Kraken AI Trading Agent is an autonomous crypto trading system built to research, validate, and execute trading strategies in a more adaptive and trustworthy way. Instead of relying on one static strategy, it maintains a research pipeline that screens multiple Kraken trading pairs, evaluates pair-specific strategy families on standardized backtests, diagnoses which candidates hold up across older and recent market windows, and promotes only the strongest ideas into a live research registry. This lets the system behave more like an evolving trading desk than a single hardcoded bot. The project is split into two major layers: research and execution. On the research side, Python modules run dense 15-minute backtests, compare performance across full 120-day, older-60-day, and recent-60-day windows, and generate proposal artifacts showing which pairs or strategies are worth promoting. On the execution side, an intraday agent runs on 15-minute intervals, reads the active registry, applies suppression logic during weak conditions, checks tradability and risk guardrails, and then paper-trades or live-trades the current validated book. n8n is used as the orchestration layer to schedule the daily research pipeline, trigger the intraday loop, and handle approval-style workflow automation, while the strategy logic itself stays in Python for transparency and reproducibility. A major focus of the system is trust and verification. The agent includes risk guardrails, portfolio-state suppression, real-time P&L tracking, research artifacts saved to disk, and ERC-8004 integration for trustless trade validation and reputation logging. The result is a trading agent that is not just trying to maximize returns, but also to make its decisions inspectable, testable, and safer to operate. In short, this project combines algorithmic trading, continuous strategy research, workflow automation, and on-chain accountability into a single hackathon-ready platform.