By Akshata Raghunatha, Partner Solutions Architect – AWS
By Pranjal Gururani, Senior Solutions Architect – AWS
By Ben Israelite, Senior Director Strategic Alliances – Workato

Workato

Many businesses use a range of applications for different functions—such as customer relationship management (CRM) systems, enterprise resource planning (ERP) software, marketing platforms, and human resources (HR) tools. These systems often don’t naturally communicate or share data with each other. This leads to data silos and inefficiencies across business processes. Workato resolves these issues by providing a unified integration platform that automates data transfer and workflow processes across different applications. It reduces manual effort, minimizes errors, ensures consistent data, and allows for more efficient and streamlined operations.

Workato, an  AWS Partner Network (APN) Partner , is a cloud-based integration and automation platform that enables organizations to connect various applications and automate business workflows without requiring extensive coding. Workato is natively built on AWS technology and offers customers inherent stability and scalability. As an AWS partner, Workato connects integrates with Amazon Bedrock, Amazon Simple Storage Service (Amazon S3), Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), Amazon Relational Database Service (Amazon RDS), Amazon Redshift, AWS Lambda and many other AWS services with on on-prem and SaaS applications automating actions to address mission-critical business needs successfully. Workato resolves these issues by providing a unified integration platform that automates data transfer and workflow processes across different applications. It reduces manual effort, minimizes errors, ensures consistent data, and allows for more efficient and streamlined operations. In this blog post, we will look at kwey features of Workato, explore several popular use cases and how Workato can help solve them and also look at a high level overview of Workato’s Architecture.

Let us start with looking at some key features that Workato platform offers:

Key Features of Workato

Integration and Automation:

• Workato allows businesses to integrate applications and automate complex workflows without the need for coding.
• It supports over 1,000+ pre-built connectors to popular SaaS applications like Salesforce, Slack, Workday, SAP, and more.

Artificial Intelligence (AI) and Machine Learning (ML) Capabilities:

• Workato incorporates AI and ML for decision-making and predictive automation, allowing workflows to be optimized based on data insights.

Recipe-Based Automation:

• Workflows, called “recipes”, are user-friendly and customizable. These recipes define the sequence of tasks to automate business processes.
• Recipes can be built using a drag-and-drop interface, enabling business and IT users to collaborate.

Enterprise-Grade Security:

• Workato emphasizes enterprise security and compliance, with features like role-based access, encryption, and support for GDPR, SOC 2, and HIPAA.

Real-Time Data Integration:

• It enables real-time data syncing between systems, which ensures up-to-date information across platforms and reduces manual data entry.

API Management:

• Workato allows users to expose existing integrations and workflows as APIs, providing easy access to internal and external stakeholders.

Scalability:

• Designed for enterprise-level usage, Workato can scale to handle large volumes of data and complex workflows while maintaining performance.

Pre-Built Solutions:

• Workato offers industry-specific solutions and connectors to accelerate deployment for common use cases in marketing, HR, finance, and IT.

Lets next look at the high level architecture of Workato Platform.

Architecture Overview

Figure 1: Workato Ecosystem

Workato’s integration platform built on AWS Cloud environment, enables seamless automation and data flow across various systems. Workato, a low-code/no-code platform, allows businesses to connect diverse applications and data sources, including API consumers, IoT devices, SaaS/cloud apps, collaboration tools, AI/ML services, and productivity applications, among others. By leveraging a wide range of connectors and Workato’s “recipe-driven” automation, organizations can automate workflows and synchronize data in real time, ensuring high-speed data flow and operational efficiency. The platform’s design scales to handle multiple data sources, ranging from on-premise systems and legacy formats to modern cloud and IoT sources, catering to complex, large-scale operations. Workato platform integrates with many AWS services like AWS Bedrock, Amazon S3, Amazon SQS, Amazon SNS, Amazon RDS, Amazon Redshift, Amazon Lambda, and many other AWS services with on-prem and SaaS applications automating actions to address mission-critical business needs successfully.

In terms of power and security, Workato’s enterprise-grade features provide robust error handling, monitoring, and high levels of data protection. AWS further enhances this setup with scalable cloud services, enabling organizations to add or scale resources according to demand while maintaining performance. The architecture’s modularity allows it to support both real-time and batch processing, ensuring speed and reliability even during peak loads. Additionally, the AWS integration offers further scalability, while the inclusion of AI/ML capabilities enhances the processing power, enabling advanced analytics and insights to optimize business workflows. It is designed to accommodate both the rapid execution of automated tasks and the robust handling of complex business events.

Let us explore several popular use cases and how Workato can help solve them.

Use Case 1: Vector embedding

Vector embedding is a technique in machine learning and natural language processing (NLP) that transforms data, such as words, images, or other objects, into a continuous, fixed-size vector of real numbers. This vector represents the object in a way that captures its essential characteristics and relationships within a high-dimensional space. In simpler terms, vector embeddings translate complex data into a set of numerical values (vectors) that machines can easily process. Machine learning engineers develop and deploy machine learning models, often using embeddings for tasks like classification, clustering, recommendation systems, or NLP tasks. They use embeddings to improve model performance by encoding features into meaningful dense vectors.

Now, let’s explore how Workato platform with Bedrock Vector embedding can streamline this process for ML engineers.

Figure 2: Workato recipe for Vector Embedding

• New file in Amazon S3: The workflow is triggered whenever a new file is uploaded to an S3 bucket, which might contain raw text data.
• Generate text embedding using Amazon Titan Embed Text V2.0 in AWS Bedrock: Once the file is uploaded, its contents are processed using Amazon Titan’s text embedding model (within AWS Bedrock). This converts the text into vector embeddings that capture semantic meaning.
• Upload file in Amazon S3: The generated embeddings are then stored as a file back in Amazon S3, making the processed data accessible for future analytics, machine learning tasks, or other downstream uses.

For data scientists, this workflow automates the transformation of raw text data into vector embeddings, leveraging AWS Bedrock’s Titan model, and efficiently stores the results in Amazon S3. It streamlines the embedding process, enabling faster experimentation and model development.

Use Case 2: Email Summarization

Customer support team often have to handle large number of inquiries and escalations. The vast amount of information stored in tickets makes it hard for the organization to extract insights from feedback, and prioritize issues based on sentiment analysis. Using Workato integrated with Amazon Bedrock, you can automate these processes.

Below Diagram shows Workato platform with Summarization.

Figure 3: Workato recipe for Email Summarization

• New email received in Outlook Mail (Real-time): The process is initiated automatically when a new email arrives in an Outlook mailbox. This could be a customer inquiry or support request.
• Summarize text using AWS Bedrock: Once the email is received, the content of the email is passed to AWS Bedrock, which uses AI models to summarize the text. This helps the customer service team quickly grasp the core message without reading long emails in full detail.
• Upload file in Amazon S3: After the text is summarized, the summary is uploaded as a file to Amazon S3 , ensuring that the summarized information is stored securely for future reference or reporting.

This automated workflow is designed to help customer service teams handle emails more efficiently by summarizing text and storing it in a structured way. It saves time, improves response speed, and provides a scalable method to manage large volumes of customer communications.

Conclusion

This blog shows examples on how Workato’s low-code, no-code iPaaS helps organizations leverage generative AI capabitliy from Bedrock to transform their business, delivering efficiency, agility, and innovation. By enabling non-technical users to build and automate workflows without the need for extensive coding expertise, Workato empowers organizations to accelerate digital transformation, reduce dependency on IT resources, and seamlessly integrate applications and data across the enterprise. Ultimately, Workato helps organizations become more agile, streamline operations, and foster greater collaboration between business and IT teams, driving measurable business outcomes and a competitive edge in the market.

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Workato – AWS Partner Spotlight

Workato is a AWS Advanced Technology Partner and AWS Competency Partner that helps businesses automate workflows and integrate application. It supports integrations across various applications like AWS, Salesforce and SAP, allowing teams to automate tasks, synchronize data, and build customized workflows. Its low-code approach makes it accessible for both technical and non-technical users.

Contact Workato | Partner Overview | AWS Marketplace