# Getting Started -------------------------------------------------------------------------------- title: "Introduction" description: "Learn about getting started with Catalyst Zia Services that provides powerful tools to implement advanced AI/ML capabilities into your application." last_updated: "2026-03-18T07:41:08.695Z" source: "https://docs.catalyst.zoho.com/en/zia-services/getting-started/introduction/" service: "Zia Services" -------------------------------------------------------------------------------- # Introduction to Catalyst Zia Services Catalyst Zia services is a suite of fully managed AI/ML-powered components that can be readily incorporated to build smart and reliable applications. These components help detect, process, or predict data that can be highly beneficial in various aspects of your business, such as in understanding your customers better, fetching valuable insights, identifying trends with your existing datasets, analyzing and extracting information from images or documents, and more. Catalyst Zia services is a part of the Catalyst development platform that bundles together multiple, on-demand, programmable backend components. These components can be easily integrated into your existing application code base, enabling you to implement advanced AI/ML capabilities into your application with minimal efforts from your end. Catalyst, as a whole, serves as a complete end-to-end solution that provides services right from an application's development and testing phases, to its deployment and monitoring phases. The setup and management of the underlying server resources utilized for these applications are entirely handled by Catalyst, thereby completely eliminating the infrastructure, maintenance costs and efforts from your end. {{%note%}}{{%bold%}}Note :{{%/bold%}} You can explore the other {{%link href="/en/" %}}Catalyst services{{%/link%}} such as {{%link href="/en/cloud-scale/getting-started/introduction/" %}}Catalyst Cloud Scale{{%/link%}}, {{%link href="/en/serverless/getting-started/introduction/" %}}Catalyst Serverless{{%/link%}}, {{%link href="/en/devops/getting-started/introduction/" %}}Catalyst DevOps{{%/link%}} and more, and the components in them. Catalyst services can either be used independently, or be integrated with one another to build highly functional and robust applications and micro services from scratch. {{%/note%}} Catalyst Zia components can be accessed from an unified and user-friendly {{%link href="https://console.catalyst.zoho.com/baas/index" %}}console{{%/link%}} that enhances your usage experience, and enriches collaboration between team members contributing to an application. You can easily test Zia components in the Catalyst console with sample data sources before implementing them in your application. This helps you understand the functionality of each component better. Catalyst also provides support for both web-based and mobile-based applications, that includes platforms such as Android and iOS. You can integrate the functionalities of the Zia components in your application seamlessly by incorporating the readily available sample {{%link href="/en/sdk/java/v1/zia-services/ocr" %}}SDK{{%/link%}} code templates in the following programming environments : * {{%link href="/en/sdk/java/v1/zia-services/ocr" %}}Java{{%/link%}} * {{%link href="/en/sdk/nodejs/v2/zia-services/ocr" %}}Node.js{{%/link%}} * {{%link href="/en/sdk/python/v1/zia-services/ocr" %}}Python{{%/link%}} These functionalities can also be accessed through their {{%link href="/en/api/code-reference/zia-services/ocr/#OCR" %}}API{{%/link%}} endpoints. You can quickly get started with Catalyst Zia using this {{%link href="/en/zia-services/getting-started/quick-start-guide" %}}quick start guide{{%/link%}}. -------------------------------------------------------------------------------- title: "Architechture" description: "Learn about getting started with Catalyst Zia Services that provides powerful tools to implement advanced AI/ML capabilities into your application." last_updated: "2026-03-18T07:41:08.695Z" source: "https://docs.catalyst.zoho.com/en/zia-services/getting-started/architechture/" service: "Zia Services" -------------------------------------------------------------------------------- # Architecture of Catalyst Zia Services A generic, end-to-end workflow of the data analysis and prediction process by various Zia components is described below : 1. When you access any Zia component from the Catalyst console, APIs, or SDKs, an API call will be triggered to the Catalyst servers, along with the input data provided by your application. Pre-trained machine learning models are pre-loaded and stored within Catalyst's servers. Based on the specific Zia component being accessed, corresponding ML models will be used for prediction. 2. The input data will then undergo pre-processing to be converted to formats recognizable by the corresponding ML model. 3. The pre-processed data is then sent for prediction to the Zia ML models, and based on the evaluation metrics specified, predicted results are returned as the response. The prediction mechanism also depends on the accuracy and volume of the data being fed. {{%note%}}{{%bold%}}Note :{{%/bold%}} Catalyst does not store any of the files you upload in its systems. The files you upload are used for one-time processing only. They are not used for ML model training purposes either. Catalyst components are fully compliant with all applicable data protection and privacy laws.{{%/note%}} -------------------------------------------------------------------------------- title: "Components" description: "Learn about getting started with Catalyst Zia Services that provides powerful tools to implement advanced AI/ML capabilities into your application." last_updated: "2026-03-18T07:41:08.695Z" source: "https://docs.catalyst.zoho.com/en/zia-services/getting-started/components-of-zia-services/" service: "Zia Services" -------------------------------------------------------------------------------- # Components of Zia Services {{%fieldset title="Test-based components" %}} {{%fieldset-card icon="automl-icon" path="/en/zia-services/help/automl/introduction/" title="AutoML"%}}Ready-to-implement, powerful Automated Machine Learning service {{%/fieldset-card%}} {{%fieldset-card icon="text-analytics-icon" path="/en/zia-services/help/text-analytics/introduction/" title="Text Analytics"%}}Recognition of sentiments, entities, keywords from text{{%/fieldset-card%}} {{%/fieldset%}} <br /> {{%fieldset title="Image-based components" %}} {{%fieldset-card icon="ocr-icon" path="/en/zia-services/help/optical-character-recognition/introduction/" title="OCR"%}}Microservice for detection and recognition of textual characters{{%/fieldset-card%}} {{%fieldset-card icon="face-analytics-icon" path="/en/zia-services/help/face-analytics/introduction/" title="Face Analytics"%}}AI-driven detection and analysis of facial features{{%/fieldset-card%}} {{%fieldset-card icon="image-moderation-icon" path="/en/zia-services/help/image-moderation/introduction/" title="Image Moderation"%}} Tool to monitor unsafe content in images{{%/fieldset-card%}} {{%fieldset-card icon="object-recognition-icon" path="/en/zia-services/help/object-recognition/introduction/" title="Object Recognition"%}}Detection and classification of objects in images{{%/fieldset-card%}} {{%fieldset-card icon="barcode-scanner-icon" path="/en/zia-services/help/barcode-scanner/introduction/" title="Barcode Scanner"%}}Microservice to extract encoded barcode content{{%/fieldset-card%}} {{%fieldset-card icon="identity-scanner-icon" path="/en/zia-services/help/identity-scanner/introduction/" title="Identity Scanner"%}}Secure validator of ID proofs and documents{{%/fieldset-card%}} {{%/fieldset%}} <br /> As depicted above, Catalyst Zia services comprises of varied components, each with a specific functionality and scope. They can be broadly classified into two categories : ### Text-based components * {{%link href="/en/zia-services/help/automl/introduction/" %}}AutoML{{%/link%}} : AutoML analyzes a set of training data that you provide and predicts the outcome of a particular subset of that data. You can train models before performing predictive analysis. This enables Zia to iterate through a variety of advanced machine learning algorithms for the training, and provide accurate results. * {{%link href="/en/zia-services/help/text-analytics/introduction/" title="Text Analytics" %}}Text Analytics{{%/link%}} : The Text Analytics component processes textual content and performs these operations on it - Sentiment Analysis, Named Entity Recognition, and Keyword Extraction. This allows you to obtain the tone of the text, the categorizations of the entities recognized from it, and the key words and phrases in it that provide a gist of the text. ### Image-based components * {{%link href="/en/zia-services/help/optical-character-recognition/introduction/" %}}OCR{{%/link%}} : OCR detects textual characters in images (printed or hand-written), and converts them to machine encoded text. * {{%link href="/en/zia-services/help/face-analytics/introduction/" %}}Face Analytics{{%/link%}} : The Face Analytics component uses image-processing capabilities and AI to detect faces in images and analyse the gender, age and emotion of the detected faces for accurate decision-making. * {{%link href="/en/zia-services/help/image-moderation/introduction/" %}}Image Moderation{{%/link%}} : The Image Moderation component detects and recognizes unsafe content in images including content indicating violence, gore, blood, weapons, drug and nudity. * {{%link href="/en/zia-services/help/object-recognition/introduction/" %}}Object Recognition{{%/link%}} : The Object Recognition component detects, locates and recognizes individual objects from the uploaded image file and returns information such as the coordinates and type of the object. * {{%link href="/en/zia-services/help/barcode-scanner/introduction/" %}}Barcode Scanner{{%/link%}} : The Barcode Scanner component scans the machine-readable encoded information in the barcodes, decodes it and returns the response. * {{%link href="/en/zia-services/help/identity-scanner/introduction/" %}}Identity Scanner{{%/link%}} : The Identity Scanner component enables you to perform secure identity checks on individuals and documents by scanning and processing various Indian ID proof documents such as Aadhaar cards, PAN cards, bank passbooks, and cheque leaves. {{%note%}}{{%bold%}}Note:{{%/bold%}} AutoML is currently not available to Catalyst users accessing from the EU, AU, IN, or CA data centers. Identity Scanner is only relevant to Indian Users and is therefore available only in the IN DC. {{%/note%}} -------------------------------------------------------------------------------- title: "Benefits" description: "Learn about getting started with Catalyst Zia Services that provides powerful tools to implement advanced AI/ML capabilities into your application." last_updated: "2026-03-18T07:41:08.696Z" source: "https://docs.catalyst.zoho.com/en/zia-services/getting-started/benefits/" service: "Zia Services " -------------------------------------------------------------------------------- # Benefits * **Boosts Customer Experience** : With powerful AI and ML components readily available to be implemented, application developers can focus more on the overall workflow and underlying core logic of the app than configuring ML features from scratch. * **Quick Seamless Integration** : You can integrate multiple Zia components into your application with ease. This can be done by implementing the component specific sample {{%link href="/en/sdk/java/v1/zia-services/ocr" %}}SDK{{%/link%}} code templates in your application's codebase, or by accessing the respective {{%link href="/en/api/code-reference/zia-services/ocr/#OCR" %}}API{{%/link%}} endpoints. This easy integration process aids in a hassle-free journey by substantially reducing your time and efforts from developing complex algorithms and code, or performing elaborate configurations. * **Test and Implement** : You can test each Zia component in the console with sample data before implementing it in your Catalyst application. This will help you gain better insights about the component's functioning and the responses generated. * **Cost savings** : With the Catalyst services being hosted on a serverless platform, the server-on-demand technology ensures that server spaces are utilized only when requests are made. Catalyst works with the pay-as-you-go model, where you are charged only for the API calls being made to access the Zia services. * **Efficiency and Error Reduction** : With highly streamlined machine learning models trained built using well-designed algorithms, the efficiency of the overall outcome is increased and the percentile prone to errors is drastically reduced. * **High performance and Scalability** : Catalyst Zia aims to provide high levels of throughput with minimal latency of requests. The scope of an application that implements Zia can be scaled easily, as the underlying infrastructure is capable of processing massive amounts of data in a streamlined manner. With its high auto-scalable capability, Catalyst's server resources are allocated on demand instantly, which can in turn manage high traffic spikes effectively. -------------------------------------------------------------------------------- title: "Use Cases" description: "Learn about getting started with Catalyst Zia Services that provides powerful tools to implement advanced AI/ML capabilities into your application." last_updated: "2026-03-18T07:41:08.696Z" source: "https://docs.catalyst.zoho.com/en/zia-services/getting-started/usecases/" service: "Zia Services" -------------------------------------------------------------------------------- # Use cases Zia components can be implemented in applications of vast domains including finance, health care, entertainment, retail, marketing, tourism, real estate, supply chain, and many more. A few effective real time use-cases of Zia services are listed below : 1. An ecommerce application that implements AutoML to provide recommendations based on the purchase patterns and the personalized interests of their customers. Barcode Scanner can be enabled in the application to fetch product information from the printed codes when customers return or exchange the products they purchased. E-KYC can also be incorporated in the application to extract the details of the AADHAAR cards or other ID proofs of the customer, and verify the same using any legal government sources, if they opt for postpaid or EMI payment schemes. 2. A payment application that uses the Identity Scanner feature to extract the credentials of the customer PAN card and verify the same with the existing information with the service provider. The application can also extract bank passbook details and cheques using the Passbook and Cheque models of Identity Scanner, and perform an Identity check when users make money transfers to bank accounts. Besides these, Facial Comparison can be implemented in this use case to verify the identities of users by comparing an uploaded photograph of theirs with the photograph in their ID proof. 3. A content review application that collates data by processing reviews that users publish in its platform after the release of movies, web series or books and uses Sentiment Analysis to analyse the emotions expressed by users in their reviews. Based on the extracted results, a group's favorite score can be generated. This can hugely benefit the audience to know the overall gist and response received by the movie or book beforehand making a purchase or booking. 4. An application linked to traffic security cameras implements OCR to read license plates of the vehicles that violate the speed limits and other traffic regulations in that locality. The data fetched from this application can be sent to the respective legal authorities, enabling them to take necessary actions on the perpetrators. 5. An application linked to the operational cameras in a retail store can implement the Object Recognition and Face Analytics feature to monitor and analyze the pattern of crowd during specific days of the week, their age, and their gender in order to gain useful insights for the store owners to best know their customer demographics.This can even be used to detect the facial emotions expressed by the customers during the launch of a new product to analyze its reception and its future scope. -------------------------------------------------------------------------------- title: "Quick Start Guide" description: "Learn about getting started with Catalyst Zia Services that provides powerful tools to implement advanced AI/ML capabilities into your application." last_updated: "2026-03-18T07:41:08.696Z" source: "https://docs.catalyst.zoho.com/en/zia-services/getting-started/quick-start-guide/" service: "Zia Services" -------------------------------------------------------------------------------- # Getting Started with Catalyst Zia Services : This section covers the overall steps involved in leveraging Zia components in your Catalyst application and building upon them. 1. **Create a project** : Access the {{%link href="https://console.catalyst.zoho.com/baas/index" %}}Catalyst console{{%/link%}} or {{%link href="/en/getting-started/quick-start-guide/#step-1-create-a-catalyst-project" %}}create a new project{{%/link%}}. After the project creation is done, you will be able to access all Catalyst services from the console. Additionally, you can also create a new project in the local environment by {{%link href="/en/getting-started/quick-start-guide/#step-4-initialize-the-project-from-the-cli" %}}initializing it from the CLI{{%/link%}}. You must first {{%link href="/en/getting-started/quick-start-guide/#step-2-install-catalyst-cli" %}}install Catalyst CLI{{%/link%}} and {{%link href="/en/getting-started/quick-start-guide/#step-3-log-in-from-your-cli" %}}log in{{%/link%}} to your remote account before you can access the Catalyst commands and work with your application locally. 2. **Accessing Catalyst Zia Services** : You can access Catalyst Zia components by navigating to the Catalyst Zia service in the left pane of the Catalyst console. You can view all text-based and image-based Zia features there, access the component of your choice, and test them instantly with sample data to get a better understanding of their functionality or the responses you would receive. 3. **Code the logic** : You can easily incorporate these Zia components, and all other required services, into your application's logic using the {{%link href="/en/sdk/java/v1/zia-services/ocr" %}}Catalyst SDK{{%/link%}} in your code for the required platform. You can also access a host of Catalyst functionalities through our component-specific {{%link href="/en/api/code-reference/zia-services/ocr/#OCR" %}}API{{%/link%}} endpoints. You can choose to build your Catalyst application by accessing and implementing the required {{%link href="/en/" %}}Catalyst components{{%/link%}} from the other services. You can build the application logic by working with the Catalyst project directory locally using an external IDE. Catalyst CLI enables you to initialize all of your project resources in the local environment directly. 4. **Test the application** : If you have built your application in Catalyst platform, you can test your application or microservice locally before deploying it to the remote console through a {{%link href="/en/cli/v1/cli-command-reference/" %}}variety of CLI commands{{%/link%}}. For example, you can test certain function types through a built-in shell in your terminal. If you test your application locally, you can deploy it to the remote console after the testing, and access the client and accessible function end-points from their {{%link href="/en/cli/v1/deploy-resources/deploy-all-resources/" %}}development URL{{%/link%}}. Note : The sequence of steps specified here might differ based on your business or application logic, or your specific use case. The flow mentioned in the deploying and testing phases of the application can be altered based on your requirements. This is a generic set of guidelines that is suitable for a typical small to mid-scale, client-based application or microservice. 5. **Host the application** : You can also host your Catalyst web application in the development environment in parallel through the {{%link href="/en/cloud-scale/help/web-client-hosting/introduction" %}}web client hosting{{%/link%}} of the CloudScale service, and monitor its performance. Using Catalyst DevOps, you can perform iterative QA tests, end-to-end integrated tests, or release an alpha version of your solution. 6. **Migrate your application to production** : After you test your application in the development environment, it can be migrated to production as described in {{%link href="/en/deployment-and-billing/environments/initial-deployment/" %}}this{{%/link%}} help page. You can continue using the DevOps components post production to monitor your application during the maintenance phase, as well as during subsequent upgrades and releases.