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eZintegrations : Integration Templates for Enterprise Applications
This repository contains a collection of eZintegrations automation templates sourced from various Enterprise Projects. These templates are designed to help automate a wide range of tasks and workflows using eZintegrations, making it easier for users to discover and use ready-made automations for various platforms and service
- Sign up with eZintegrations
- Download any preferred automation template from this repository absolutely FREE!
- Import into eZintegrations App
- Change the Credentials of Data Source and Data Target with your apps
- Schedule the frequency or Use Event Triggers and Start the Integration Bridge : Hola ! you are Live
- Any Enterprise Applications Integrations : SaaS, On-Premises Apps, RDBMS database, Datawarehouse, NoSQL DBs, Vector Databases, Digital Marketing, Social and more
- Any Protocols : HTTPS ( REST API, SOAP API, GraphQL API), Webhook, Websocket, TCP, SMTP
- Databases : Oracle, SAP, Teradata, MySQL, MSSQL and more...
- Faster time to automation. Do integration in days and not weeks and months. Enterprises never did integrations in days and weeks. It was always in months
- See what's possible. Most Enterprise users struggle to identify as what to automate and how to make their business process easy.
- If Budget is a contraint for Enterprise team, eZintegrations platform solve this. Teams can start as low as $20/month with a Single Integration Service with unlimited data streaming
- These eZintegrations templates makes Consulting cost almost negligible. Unlike other Enterprise Teams heavily invest in Consulting for development, configuration, workshops and UAT. These templates makes breeze, go straight to testing and make it Live
Documentation is available here
Have a question? Ask in our Community Forum
| Name | Description | Team | Link |
|---|---|---|---|
| Legal Document Classification using AI | Documents are extracted from SharePoint and processes them without any loss of data.The integration service intelligently reads and interprets the content of each document regardless of format and automatically classifies and routes them to the appropriate target folders in the SFTP destination | Legal | Link |
| Pharma Document Understanding using AI | Unstructured pharmaceutical data is extracted from SharePoint and processed using AI Document Understanding. Key information is intelligently identified and transferred to the Data Lake for downstream business processing. This streamlines document handling and enhances data accessibility for pharmaceutical operations. | Pharma | Link |
| Document Classification of Zipped files using AI | AI extracts and classifies NDA legal documents from ZIP files stored in SharePoint. Using AI document understanding, it processes the content and transfers the structured output to Datalake for further legal analysis and integration. | Legal | Link |
| AI Document Understanding from SharePoint to Datalake | Extracts unstructured data from files stored in SharePoint, involves scanning content such as PDFs, Word documents, or presentations in Manufacturing Domain using AI document understanding. The extracted data is then transformed into clean, structured formats like JSON or tables, and routed to DataLake for analytics. | Manufacturing | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| S3 Group Permissions Audit to Database | Extracts group permission settings and access control details from AWS S3 to monitor who has access to various resources. It processes this security information to ensure permissions are accurate and comply with organizational policies. The data is then synchronized into a Microsoft SQL Server database for centralized storage. | IT Operations | Link |
| AWS S3 File Actions to Database | Captures detailed file/folder level activities from AWS S3, such as Create, Update, and Delete. It then logs this information into a SQL Server database for centralized monitoring and analysis. The data helps to track usage patterns, detect anomalies, and support auditing requirements. By consolidating these logs, it enables efficient data processing and operational insights across the organization. | IT Operations | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Acumatica Stockitems to Google Sheet | Exports stock item data from Acumatica ERP to Google Sheets, enabling easy tracking, sharing, and lightweight analysis of inventory information. It helps teams quickly access upto date stock details without complex database queries.The service runs on a predefined schedule and updates the sheet automatically, eliminating the need for manual intervention | ERP | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Amazon Settlement Report to Database | Settlement and transactional data from Amazon Seller Central is automatically transferred to the Oracle Database. The integration processes a wide range of financial reports including orders, fees, and adjustments to enable accurate and efficient reconciliation. All data is securely structured and stored, ensuring seamless access for downstream accounting operations and comprehensive financial reporting. | Accounts Payable | Link |
| Amazon sales order to Database | Transfers sales order data from Amazon Seller Central to Oracle Database. It captures key details such as order items, pricing, and customer information, and processes them into a structured format. The integrated data enables downstream operations like inventory management, financial reconciliation, and sales analysis. | eCommerce | Link |
| SAP to Amazon Ship confirmation | The SAP to Amazon ship confirmation process involves transmitting shipment details from SAP to Amazon after goods are dispatched. The system collects the Data from ERP like SAP and send the ship confirmation data to Amazon. This enables Amazon to update order status, collaborate with carriers, and initiate payment processing. It's a key step in the workflow to ensure smooth logistics and accurate delivery tracking. | eCommerce and ERP | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| File Action logs from Azure Storage to Database | Captures detailed file actions and events occurring within Azure Storage, such as file uploads, modifications, and deletions. It processes these logs to ensure accurate tracking of user activity and file changes. The collected data is then securely transferred and stored in a Microsoft SQL Server database. This enables comprehensive audit trails for compliance and governance purposes. Ultimately, it supports monitoring, reporting, and analysis of storage activity across the organization. | IT Operations | Link |
| File Scanning for PII data from Azure to Database | Scans the files stored in Azure for any PII data like SSN, Driving license Number etc.It checks each and every document type stored in Azure and gives us the output for the count on number of PII data found in each documents along with document information. The findings are then updated into a Microsoft SQL Server database to maintain a centralized log. This enables ongoing monitoring, reporting, and analytics of file compliance status. Ultimately, it helps ensure data integrity, regulatory adherence, and supports proactive risk management. | IT Operations | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Cerner patient data to Datalake | Transfers patient data from Cerner systems in the standardized FHIR format into Data Lake. The Patient data along with required information is fetched from cerner , the data gets transformed into FHIR format in Data operation step and the it is sent to the Target Database system. The integration enables centralized storage of Patient data, facilitating advanced analytics, reporting, and interoperability across healthcare applications to improve patient care and operational efficiency. | Healthcare | Link |
| EHR to NetSuite Integration | Transferring electronic health records (EHR) from AllScript Sunrise into NetSuite to support both financial and operational processes.The data is fetched from sunrise EHR system , the Data gets converted to Netsuit payload and gets ingested with 3 simple steps. This enables seamless data flow between clinical systems and enterprise resource planning for improved efficiency and decision-making. | Healthcare | Link |
| EHR Patient Data to database | Patient data from EHR is fetched along with required Data which is needed.It is done to enhance healthcare analytics. It extracts structured records like demographics, treatment history, lab results, and billing details transforms them to align with Datalake’s schema, and ingests them via secure Flow | Healthcare | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| E-Way Bill Generation and Routing | The E-Way Bill is generated after the invoice is approved and the Invoice Reference Number (IRN) is successfully fetched from the e-invoicing system. This IRN serves as a prerequisite for E-Way Bill creation. Based on the approved invoice, the system automatically generates the E-Way Bill Number (EBN) along with its validity period and expiration time and send the Data to Database/ERP, ensuring compliance and traceability during the movement of goods | Accounts Payable | Link |
| E-invoice Generation and Routing | Connects ERP systems, government portals (like IRP and E-Way Bill), and enterprise databases. It facilitates automated exchange and transformation of structured data such as invoice JSON from ERP and gets the invoice Approved with IRN, QR Code, Signature. The bridge ensures real-time synchronization, statutory compliance, and end-to-end visibility across financial and operational workflows. It is designed to handle high-volume transactions with validation, error handling, and audit logging. | Accounts Payable | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Lead Data Enrichment and Scoring on ICP | Lead data is sourced from a Google Sheet containing fields such as name, email, industry, and location. Using AI operations, the system analyzes each lead’s industry and evaluates its alignment with the Ideal Customer Profile (ICP) based on a simple English prompt. The AI assigns a relevance score to each entry, and the Google Sheet is automatically updated with new columns reflecting these scores—enabling quick identification of high-potential leads aligned with your ICP. | Marketing / Sales | Link |
| Enriching and filtering different Lead data into ICPs | Lead information such as name, email, and company is captured from Sheet 1, while company-related details like address and city are sourced from Sheet 2. Using intelligent matching logic based on the company name, relevant data from Sheet 2 is mapped and enriched into Sheet 1. This process ensures that each lead record in Sheet 1 is supplemented with accurate location data, enabling a more complete and actionable dataset for outreach or analysis. | Marketing / Sales | Link |
| Linkdin User Profile Enrichment | Uses Google Sheets as the data source where fields like Name and Linkedin URL are stored Once the data is retrieved, it is processed through an Apify actor to enrich existing fields such as Name and LinkedIn URL, while also appending new fields like the user's current organization, location, profile description, company name, and company website. | Marketing / Sales | Link |
| Linkdin User Latest Activity | Uses the Google Sheets to extract user names and LinkedIn URLs, then employs Apify actors to scrape recent LinkedIn activity—likes, comments, and posts. This data is enriched to generate icebreakers using AI, which are written back to the sheet. The result is a fully automated workflow that transforms basic contact data into personalized sales intelligence for high-conversion email outreach. | Marketing / Sales | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Netsuite data to database | Automated transfer of Data from Oracle NetSuite into an Oracle Database to support reporting and Analytics. It extracts critical business information such as invoices, sales orders, customer records, and financial transactions—from NetSuite, transforms the data into a structured format, and loads it into the Oracle Database on a scheduled or event-driven basis. | ERP | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Oracle Planning Cloud data to Database | Consolidates strategic financial data by moving planning and budgeting records from Oracle Planning Cloud into Oracle Database. It extracts datasets like forecasts, allocations, cost centers, and budget versions from source being Oracle planning cloud, Extracts the Data , transforms and then formatted to align with Oracle DB’s schema for centralized storage. | Finance | Link |
| Oracle PlanningCloud partner sites to Database | Facilitates granular planning by loading partner site specific details from Oracle Planning Cloud into Oracle Database. It extracts relevant data such as forecast allocations, resource needs, timelines, and site identifiers using APIs. The extracted content is then formatted to match Oracle DB's schema and ingested. Once centralized, this data supports sitelevel reporting, performance tracking, and more accurate planning across distributed partner locations. | Finance | Link |
| Oracle PlanningCloud itemdata Integration to Database | Ensures manufacturing and cost operations are driven by accurate and centralized Bill of Materials (BOMs) data. BOM details including item hierarchies, component quantities, cost structures, and production configurations are extracted from Oracle Planning Cloud using APIs. The data is then cleaned, transformed to match Oracle Database schema, and ingested. | Finance | Link |
| Oracle PlanningCloud BOM integration to Database | Streamlines manufacturing and cost analysis by transferring Bill of Materials (BOMs) data from Oracle Planning Cloud into Oracle Database. BOM details such as item hierarchies, component quantities, cost breakdowns, and production configurations are extracted via APIs. The data is cleaned and mapped to Oracle DB schemas through , enabling accurate downstream processes like material requirements planning (MRP), cost estimation, and production scheduling. This ensures consistent and centralized insights for manufacturing operations. | Manufacturing | Link |
| Oracle PlanningCloud BOM component sync to Database | Enables detailed assembly analysis by transferring Bill of Materials (BOM) component level data from Oracle Planning Cloud to Oracle Database. It extracts individual component attributes such as part numbers, quantities, cost values, and dependency relationships using APIs. The data is then transformed and mapped to Oracle DB schemas, allowing downstream systems to conduct precise cost modeling, production planning, and resource allocation based on each assembly's structural composition. | Manufacturing | Link |
| Oracle PlanningCloud item categorysync to Database | Ensures consistent product classification by importing item category structures from Oracle Planning Cloud into Oracle Database. It extracts hierarchical category datasuch as groupings, parent child relationships, and classification codes via APIs. These structures are then cleaned, transformed, and mapped to Oracle DB schemas. | Product / Inventory | Link |
| Oracle PlanningCloud categorysetsync to Database | Promotes consistent item grouping by synchronizing category set data from Oracle Planning Cloud into Oracle Database. It retrieves structured taxonomy such as category names, set definitions, and group associations using APIs. The extracted data is transformed to match Oracle DB schema, ensuring standardized classification across inventory, procurement, and analytics systems. | Product / Inventory | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Biometric Devices to OTL timecard integration | Automates workforce time tracking by syncing biometric attendance logs with Oracle HCM’s Oracle Time and Labor (OTL) system. The process begins with capturing time stamped attendance data such as checkin/checkout times and employee IDs from biometric devices. These logs are cleaned, formatted, and mapped to OTL’s timecard schema. Once uploaded, the data triggers automatic timecard creation, reducing manual input and ensuring accurate payroll and compliance reporting. | HR / Payroll | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Oracle Fusion Products to Shopify | Transfer of product data from Oracle Fusion to Shopify, ensuring catalog accuracy and realtime inventory visibility. Product attributes like SKUs, descriptions, pricing, and stock levels are extracted from Oracle Fusion and formatted according to Shopify's GraphQL schema. Through GraphQL queries and mutations, the data is efficiently pushed to Shopify’s backend, allowing instant updates across the storefront. | eCommerce | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| EZPass data from SFTP to Database | Ensures accurate handling of EZPass toll data for financial integrity and reporting. It begins by securely retrieving transaction files via SFTP, a reliable protocol for transferring sensitive data. These files are then loaded into an Oracle database, where the data is parsed and organized for downstream accounting functions. | Accounts | Link |
| EZPass data from SFTP to CRM | Involves importing EZPass transactional data stored in SFTP into a centralized CRM system. By streamlining data from toll usage records, it enables a structured view of customer travel behaviors. The CRM then analyzes this data to uncover patterns in engagement, mobility trends, and route preferences. This helps enhance targeted outreach, improve service offerings, and personalize customer interactions based on actual travel activity. | Accounts | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| Shopify Customer Data to Acumatica | Syncs customer data from Shopify to the Acumatica ERP system to ensure unified and upto date customer records. It supports order processing and improves data consistency across sales and finance functions. By automating this integration, it reduces manual data entry and enhances operational efficiency. | eCommerce | Link |
| Shopify Orders to Acumatica ERP | Transfers order data from Shopify into Acumatica ERP as sales orders, enabling streamlined order fulfillment and processing. It ensures accurate synchronization of sales transactions between the eCommerce platform and the ERP system, improving order management and reducing manual efforts. | eCommerce | Link |
| NetSuite to Shopify GraphQL Integration | Synchronizes essential ERP data from Oracle NetSuite to Shopify using GraphQL APIs. It enables realtime data exchange between systems, ensuring Shopify’s storefront reflects upto date inventory, pricing, and product details from NetSuite. | eCommerce | Link |
| Shopify Products to database using Graphql | Fetches product data from Shopify using GraphQL with pagination to handle large datasets efficiently, then stores the retrieved information into an Oracle Database for detailed analysis and reporting. | eCommerce | Link |
| Shopify data to Database | Integrates Shopify data with Oracle Database to support comprehensive analysis and reporting of product and sales information, enabling better business insights and decisionmaking. | eCommerce | Link |
| Shopify customer data to database | Captures customer data from Shopify including contact details, purchase history, preferences, and account identifiers and transfers it into Oracle DB for enhanced business intelligence. The data is pulled via Shopify's API, then transformed to align with Oracle’s database schema. Once Ingested, it enables centralized profiling, segmentation, and advanced analytics across marketing, sales, and support functions. | eCommerce | Link |
| Shopify Orders to Oracle Fusion Sales Order | Captures order data such as product details, customer info, pricing, and quantities from Shopify via its API. The data is then transformed to align with Oracle Fusion SCM’s structure and mapped to corresponding sales order objects. Once ingested, these orders trigger downstream processes like inventory adjustments, fulfillment coordination, and logistics updates, resulting in end to end visibility across e-commerce and supply chain systems. | eCommerce | Link |
| Shopify Customers data to Oracle fusion Account | Aligns customer data across systems to create a unified account view within Oracle Fusion CX. It extracts records from Shopify such as contact details, purchase behavior, account identifiers, and communication preferences via Shopify’s API. The data is then formatted and mapped to Oracle Fusion CX’s schema. Once ingested, it supports 360degree customer profiles that enhance sales, service, and marketing engagement across enterprise touchpoints. | eCommerce | Link |
| Name | Description | Team | Link |
|---|---|---|---|
| ERP Ship Confirmation to Walmart | Transfer the Ship confirmation data for Orders from SAP to Microsoft SQL Server acting as walmart. The ship Confirmation from SAP is fetched using Odata API, the data is transformed and converted to schema of walmart and database and ingested automatically as per the scheduled Set. | eCommerce | Link |
| Walmart Orders to ERP | Sales data are extracted from Walmart and loads it into Microsoft SQL Server acting as ERP. The data is processed for accuracy and consistency to support business reporting and operations. This integration helps in realtime tracking. | eCommerce | Link |
| ERP Product sync with walmart | Transfers product data from Walmart to ERP ensuring synchronization between the two platforms. It helps to maintain accurate product information such as inventory, pricing, and availability in the SAP system and walmart for seamless operations. | eCommerce | Link |
| ERP Item sync to Walmart | Items data synced from ERP to Microsoft SQL Server acting as Walmart. It ensures product details are consistently updated across systems for accurate listings and inventory management. | eCommerce | Link |
| Walmart Inventory to ERP sync | Synchronizes inventory data from Walmart to Microsoft SQL Server acting as ERP, ensuring upto date stock levels and product availability are maintained in the database. The integration supports accurate inventory management, helps prevent stockouts or overselling, and enables operational teams to make informed decisions regarding replenishment and sales planning. | eCommerce | Link |