New features and enhancements

New recipes

Amazon Bedrock Chat with File using Guide

Use the recipe to ask questions to the Amazon Bedrock Large Language Model (LLM) based on the uploaded file's contents using a guide.

Amazon Bedrock Chat with History

Use the recipe to maintain chat history in a file and use it as context for the next user query and the Large Language Model's (LLM) response.

Amazon Bedrock Prompt Chaining

Use the recipe to design prompt chains and provide the desired responses from a Large Language Model (LLM).

Azure AI Search Ingestion Automation with ADLS

Use the recipe to create an index, data source, and indexer for the existing files in Amazon Data Lake Storage (ADLS), populate the index with the data, and then return the documents.

Azure OpenAI Prompt Engineering

Use the recipe to design prompts for Azure OpenAI. The recipe can use a guide or an HTTP request to submit prompts and receive responses from the Large Language Model (LLM).

Chat with Amazon Bedrock Knowledge Base

Use the recipe to ask questions based on the contents of the Amazon Bedrock Knowledge Base.

Create Amazon Bedrock Knowledge Base and Data Source using Guide

Use the recipe to automatically create a knowledge base and resources when the file is uploaded, and how to ask questions to the Amazon Bedrock Large Language Model (LLM) based on an uploaded file's content using a guide.

Ingest Files to Azure AI Search Index using Guides

Use the recipe to upload files to the Amazon Data Lake Storage (ADLS) container and run the indexer automatically to populate the index with the data from the uploaded files.

Omni Channel Order Management

Use the recipe to create general sales order objects from different channels.

Procure to Pay with Coupa and NetSuite

Use the recipe to generate invoice data for the approved Coupa purchase order based on a webhook request from Coupa.

Serialize Swift Messages with Secure Signatures

Use the recipe to convert Swift XML format messages into structured Swift messages, and securely sign the messages using JSON Web Tokens (JWT).

Simple RAG Consumption using Azure OpenAI with DataSources

Use the recipe to prepare and send requests to the Azure OpenAI LLM with the context.

Simple RAG Consumption with Azure OpenAI and AI Search

Use the recipe to receive a query from the user, convert it into vectors, form the context, and return a comprehensive response using a Large Language Model (LLM).

Simple React AI Agent with Azure OpenAI

Use the recipe to use Google Search to gather information, perform tasks, and answer user queries.

Synchronize Salesforce Incidents with ServiceNow Incidents based on Platform Events

Use the recipe to synchronize Salesforce incidents with ServiceNow incidents.

Update Amazon Bedrock Knowledge Base

Use the recipe to update the existing Amazon Bedrock knowledge base using the Amazon S3 data source and provide notification status.

New Connectors

Azure AI Search Connector

Azure AI Search Connector is used to manage and query indexes and documents, and manage other resources on a search service.

Google Vertex AI Connector

Google Vertex AI Connector is used to easily integrate Vertex AI with various data sources and tools, increasing the functionality and reach of your machine learning workflows. You can use a Google Vertex AI connection to integrate with various data sources and services, and build comprehensive and flexible machine learning workflows.

Jira Connector

Jira Connector performs CRUD operations, such as create, read, update, and delete, on existing resources, such as issues, tasks, and user stories in Jira. You can use the Jira Connector to connect to Jira, read data, write data, and integrate Jira with other applications, such as Salesforce. You can also read data from other applications and write to JIRA. You can create custom fields in JIRA. You can use the Jira Connector to read the custom attributes of an object.

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