Workflow Templates

This minimal utility workflow connects to the SAP Business One Service Layer API to verify login credentials and return the session ID. It's ideal for testing access or using as a sub-workflow to retrieve the B1SESSION token for other operations. ++⚙️ HOW IT WORKS:++ 🔹 1. Trigger Manually The workflow is initiated using a Manual Trigger. Ideal for testing or debugging credentials before automation. 🔹 2. Set SAP Login Data The Set Login Data node defines four key input variables: sap_url: Base URL of the SAP B1 Service Layer (e.g. https://sap-server:50000/b1s/v1/) sap_username: SAP B1 username sap_password: SAP B1 password sap_companydb: SAP B1 Company DB name 🔹 3. Connect to SAP A HTTP Request node performs a POST to the Login endpoint. The body is structured as: { "UserName": "your_sap_username", "Password": "your_sap_password", "CompanyDB": "your_sap_companydb" } If successful, the response contains a SessionId which is essential for authenticated requests. 🔹 4. Return Session or Error The response is branched: On success → the sessionID is extracted and returned. On failure → the error message and status code are stored separately. ++🛠 SETUP STEPS:++ 1️⃣ Create SAP Service Layer Credentials Although this workflow uses manual inputs (via Set), it's best to define your connection details as environment variables for reuse: SAP_URL=https://your-sap-host:50000/b1s/v1/ SAP_USER=your_sapuser SAP_PASSWORD=your_password SAP_COMPANY_DB=your_companyDB Alternatively, update the Set Login Data node directly with your values. 2️⃣ Run the Workflow Click "Execute Workflow" in n8n. Watch the response from SAP: If successful: sessionID will be available in the Success node. If failed: statusCode and errorMessage will be available in the Failed node. ++✅ USE CASES:++ 🔄 Reusable Login Module Export this as a reusable sub-workflow for other SAP-integrated flows. 🔐 Credential Testing Tool Validate new environments, test credentials before deployment.

This workflow stores responses form responses of Typeform in Airtable. The workflow also sends the response to a channel on Slack. You will have to configure the Set node if your form uses different fields.

Vector Database as a Big Data Analysis Tool for AI Agents Workflows from the webinar "Build production-ready AI Agents with Qdrant and n8n". This series of workflows shows how to build big data analysis tools for production-ready AI agents with the help of vector databases. These pipelines are adaptable to any dataset of images, hence, many production use cases. Uploading (image) datasets to Qdrant Set up meta-variables for anomaly detection in Qdrant Anomaly detection tool KNN classifier tool For anomaly detection The first pipeline to upload an image dataset to Qdrant. 2. This is the second pipeline to set up cluster (class) centres & cluster (class) threshold scores needed for anomaly detection. The third is the anomaly detection tool, which takes any image as input and uses all preparatory work done with Qdrant to detect if it's an anomaly to the uploaded dataset. For KNN (k nearest neighbours) classification The first pipeline to upload an image dataset to Qdrant. The second is the KNN classifier tool, which takes any image as input and classifies it on the uploaded to Qdrant dataset. To recreate both You'll have to upload crops and lands datasets from Kaggle to your own Google Storage bucket, and re-create APIs/connections to Qdrant Cloud (you can use Free Tier cluster), Voyage AI API & Google Cloud Storage. [This workflow] Setting Up Cluster (Class) Centres & Cluster (Class) Threshold Scores for Anomaly Detection Preparatory workflow to set cluster centres and cluster threshold scores so anomalies can be detected based on these thresholds. Here, we're using two approaches to set up these centres: the "distance matrix approach" and the "multimodal embedding model approach".

This workflow performs basic XOR-based encryption and decryption using a custom password. It is intended to be triggered by another workflow and processes structured input in JSON format. Input Structure The workflow expects a single array of objects with the following fields: action-type: either "encrypt" or "decrypt" key: the password used for encryption and decryption data: the content to encrypt or decrypt Example: Encryption Input [ { "action-type": "encrypt", "key": "Password", "data": "Hello, this is a secret message" } ] Example: Decryption Input [ { "action-type": "decrypt", "key": "Password", "data": "ChwGAQceF15eE2QXFRcUagxGVgV8TBoNBA4VQVoQZkwVUhImU1FTEg==" } ] Output The output returns an array of results, each containing either the encrypted string (base64 format) or the decrypted plain text. Use Case This workflow is useful for simple internal message encoding, data obfuscation, or testing purposes. It is not recommended for securing sensitive or personal data, as XOR encryption is not cryptographically secure. The workflow logic is written in JavaScript using n8n Function nodes, without any external dependencies.

Send a simple JSON array via HTTP POST and get an Excel file. The default filename is Export.xlsx. By adding the (optional) request ?filename=xyz you can specify the filename. NOTE: do not forget to change the webhook path!

This workflow allows you to add candidates’ profile assessments to Notion before an interview. Prerequisites Add an input field on your Calendly Invite page where the candidate can enter their LinkedIn URL. Create credentials for your Calendly account. Follow the steps mentioned in the documentation to learn how to do that. Create credentials for Humantic AI following the steps mentioned here. Create a page on Notion similar to this page. Create credentials for the Notion node by following the steps in the documentation. Calendly Trigger node: This node will trigger the workflow when an interview gets scheduled. Make sure to add a field to collect the candidates' LinkedIn URL on your invite page. Humantic AI: This node uses the LinkedIn URL received by the previous node to create a candidate profile in Humantic AI. Humantic AI1: This node will analyze the candidates' profile. Notion node: This node will create a new page in Notion using the information from the previous node.

This is Workflow 1 in the blog tutorial Database activity monitoring and alerting. Prerequisites A Postgres database set up and credentials. Basic knowledge of JavaScript and SQL. Nodes Cron node starts the workflow every minute. Function node generates sensor data (sensor id (preset), a randomly generated value, timestamp, and notification (preset as false) ) Postgres node inserts the data into a Postgres database. You can create the database for this workflow with the following SQL statement: CREATE TABLE n8n (id SERIAL, sensor_id VARCHAR, value INT, time_stamp TIMESTAMP, notification BOOLEAN);

This workflow demonstrates the use of the HTTP Request node to upload binary files for form-data-multipart type. This example workflow updates the Twitter banner. HTTP Request node: This node fetches an image from Unsplash. Replace this node with any other node to fetch the image file. HTTP Request1 node: This node uploads the Twitter Profile Banner. The Twitter API requires OAuth 1.0 authentication. Follow the Twitter documentation to learn how to configure the authentication.

This workflow provides a simple approach to counting the items returned by a node. It uses a Set node with the Execute Once option: The expression uses $input.all() (documented here) to fetch all incoming items at once, and .length (documented for example here) to count them.

This workflow allows you to validate emails stored in a table using the Mailcheck node. Airtable node: This node will list all the records from a table. Based on your use case, you might want to replace this node. Mailcheck node: This node will check the emails that got returned by the previous node. Set node: We will use the Set node to ensure that only the data that we set in this node gets passed on to the next nodes in the workflow. Airtable1 node: This node will update the Valid field in the table. Based on your use case, you might want to replace this node.

Workflow Information 📌 Purpose 🎯 The intention of this workflow is to integrate New Shopify Orders into MS Dynamics Business Central: Point-of-Sale (POS):** POS orders will be created in Business Central as Sales Invoices given no fulfillment is expected. Web Orders:** This type of orders will be created as Business Central Sales Orders. How to use it 🚀 Edit the "D365 BC Environment Settings" node with your own account values (Company Id, Tenanant Id, Tax & Discount Items). Go to the "Shopify" node and edit the connection with your environment. More help here. Go to the "Lookup Customers" node to edit the Business Central connection details with your environment settings. Set the required filters on the "Shopify Order Filter" node. Edit the "Schedule Trigger" node with the required frequency. Useful Workflow Links 📚 Step-by-step Guide/ Integro Cloud Solutions Business Central REST API Documentation Video Demo Need Help? Contact me at: ✉️greg.lopez@integrocloudsolutions.com 📥 https://www.linkedin.com/in/greg-lopez-08b5071b/

Ghost + Sendy Integration Está es una integración del CMS Ghost hacia Sendy Sendy ( www.sendy.co ) Ghost ( www.ghost.org ) Con esta integración podrás importar los miembros del CMS Ghost en su nueva versión que incluye la parte de Membresía hacía el Software de newsletter sendy. Está integración además nos avisa si se ha registrado un nuevo miembro via telegram. Para realizar esta customización es necesaria la creación de una custom integration en Ghost. Para ello desde el panel de Administración vamos a CUSTOM INTEGRATIONS / + Add custom Integration Una vez allí nos solicitará un nombre le ponemos el que queramos y añadimos un nuevo Hook: En Target URL debe ir La url que nos genera nuestro webhook dentro de n8n: Pegamos la URL y acamos de rellenar los datos del HTTP REQUEST1 con los datos de nuestra lista rellenando los campos. api_key list Que encontaras en tú instalación de Sendy Por último faltara añadir las credenciales de Telegram de Nuestro BOT ( https://docs.n8n.io/credentials/telegram/ ) e indicar el grupo o usuario donde queremos que notifique. Saludos,