By harnessing the potential of AI and ML, organizations can achieve enhanced efficiency, accuracy, and productivity. In this article, we will explore the various applications and benefits of leveraging AI and ML in workflow automation, along with case studies and best practices.

Understanding AI and ML in Workflow Automation

To comprehend the impact of AI and ML in workflow automation, it’s crucial to grasp their underlying concepts. Artificial intelligence refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence.

Machine learning, on the other hand, focuses on developing algorithms that allow systems to learn and improve from data without explicit programming. When integrated into workflow automation, AI and ML technologies provide intelligent automation capabilities that can revolutionize business processes.

It can help companies not only automate repetitive tasks and improve decision making, but also predict outcomes of workflows by identifying potential problems and suggest solutions for them.

Improving Workflow Efficiency and Accuracy

AI and ML bring remarkable improvements to workflow automation by enhancing efficiency and accuracy. Through intelligent decision-making and automation of repetitive tasks, businesses can save time and reduce errors.

For instance, intelligent document processing systems can automatically extract and categorize information from documents, eliminating the need for manual data entry and reducing processing times significantly.

AI can be used to make decisions about how to automate business workflows. For example, AI can be used to decide which tasks should be automated, how they should be automated, and when they should be automated.

ML algorithms can learn from patterns in data, allowing systems to make accurate predictions or recommendations, leading to better decision-making and optimized workflows. Machine learning can be used for detecting patterns, classifying information and predict outcomes with high reliability.

Enhancing Personalization and Customer Experience

By using AI and ML in workflow automation, organizations can personalize customer experiences and deliver targeted solutions. AI-powered chatbots and virtual assistants can provide instant responses to customer inquiries, improving engagement and satisfaction.

ML algorithms can analyze customer data to generate personalized recommendations and offers, leading to enhanced customer experiences and increased conversions.

Workflow automation driven by AI and ML enables organizations to cater to individual preferences at scale, delivering a seamless and tailored customer journey.

AI & ML in Action

Several companies have successfully leveraged AI and ML in workflow automation to achieve significant outcomes. For instance, a healthcare provider implemented AI-powered image recognition systems to automate the analysis of medical images, resulting in faster and more accurate diagnoses.

In the finance industry, ML algorithms are used to detect fraudulent activities by analyzing vast amounts of transaction data. The invoice and bills are also automatically categorized after scanning them. E-commerce giants employ AI-driven recommendation engines to personalize product suggestions and improve customer engagement.

Here are some more ways in which AI and ML is helping companies:

Healthcare industry: AI is being used to automate tasks such as scheduling appointments, processing insurance claims, and managing patient records.
Manufacturing industry: AI is being used to automate tasks such as quality control, inventory management, and predictive maintenance.
Financial services industry: AI is being used to automate tasks such as fraud detection, credit scoring, billing, invoicing and customer service
Retail: AI is used to automate tasks such as product recommendations, pricing, and inventory management.
Logistics: AI can be used to automate tasks such as tracking shipments, managing inventory, and optimizing routes.
Human resources: AI is used to automate tasks such as onboarding new employees, training them, managing employee benefits, and tracking employee performance.
Customer service: AI can be used to automate tasks such as answering customer questions, resolving complaints, and providing support.

Best Practices for Implementing AI and ML in Workflow Automation

When integrating AI and ML into workflow automation, organizations should consider a few best practices. These include data quality and preparation, selecting appropriate AI and ML technologies, ensuring ethical and transparent practices, and ongoing monitoring and evaluation.

Collaboration between domain experts and data scientists is vital to understanding business requirements and developing effective AI and ML models. Organizations should also focus on user adoption and change management to ensure successful implementation and maximum benefits.

Conclusion

Artificial intelligence and machine learning offer immense potential to transform workflow automation. By embracing these technologies, organizations can unlock new levels of efficiency, accuracy, personalization, and customer satisfaction.

As businesses continue to evolve, leveraging AI and ML in workflow automation will become a critical competitive advantage in achieving operational excellence.

Kreyon Systems provides AI-based business software implementation for improved productivity, efficiency & financial automation. For any implementation queries, please get in touch with us.

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Enterprise software development often involves creating large scale, complex systems that are critical to an organization’s operations. Getting it right takes commitment, due diligence and ever evolving set of skills to deliver the most compelling results. Here’s a look at some of the best practices for enterprise application services:

1. Identify the Test Scenarios Inline with the Business Priorities:

By automating user testing for enterprise software services, you can improve the overall quality of the software, reduce the time and cost of testing, and speed up the delivery of new features and updates.

Identify the critical user test scenarios that need to be automated, such as user flows, error conditions, and edge cases. Involve a test driven development plan to ensure user scenarios and key outcomes are tested early in the development process.

Integrate automated testing with the enterprise software development to improve the quality of the deliverables. This may involve configuring the testing tool to interact with the software services using APIs, web services, or other integration methods.

Run the automated tests on a regular basis to identify issues and bugs as early as possible. This can help ensure that the enterprise software services are working as intended and meet the required quality standards as per intended business outcomes.

Fix any issues and bugs identified through the automated testing process. This may involve making changes to the enterprise software services, the automated test scripts, or both. Also, once automation testing is done, the application can be used by the early end users for their inputs and validations.

2. Enterprise Application Integration

Enterprise Application Integration (EAI) is the process of connecting different software applications and systems within an organization to enable them to communicate and exchange data seamlessly. The goal of EAI is to create a unified, integrated view of an organization’s business processes and data by linking disparate systems and applications.

EAI involves a variety of techniques and technologies, including middleware, APIs, web services, and messaging protocols, to enable different systems to communicate and exchange data. It often involves creating a central data repository or hub that can be used to store and manage data from different applications.

EAI can provide a range of benefits to organizations, including increased efficiency and productivity, improved decision-making through better data visibility, and enhanced customer experience through more seamless and integrated processes. EAI can also reduce data duplication and improve data quality by enabling data to be shared and managed more effectively across different applications and systems.

3. Data Quality Measures

Data quality is a crucial consideration for enterprise software development. Poor data quality can lead to inaccurate or incomplete information, which can negatively impact business operations and decision-making.

Develop a data governance framework that defines data standards, policies, and procedures for data management, quality control, and privacy.

Understand and define clear metrics for measuring data quality, such as accuracy, completeness, consistency, and timeliness for your enterprise application. For e.g. accounting data should have all elements clearly spelt out to generate balance sheet, profit & loss and other financial reports for the business.

All data sources should be mapped accurately to provide the right information in realtime. Data quality issues can cause malfunctioning of an application, for e.g. missing values, duplicate records, and inconsistent data.

Use automatic testing procedures to develop data monitoring processes to identify and address data quality issues in real-time. Once the data sources are mapped and integrated, end-users can then ensure that the data is relevant and useful to the business.

4. Leverage Latest Technologies

Enterprise software development is getting incrementally more sophisticated thanks to the new developments. Today, you can build and query systems to answer your questions. You can use AI to analyze user behavior and feedback to improve user experience by providing personalized recommendations, search results, and notifications.

The technology tools can also be used to improve security by detecting anomalies, identifying potential issues, and mitigating risks. AI based software leverages data-driven insights and recommendations to facilitate decision making, such as identifying trends, detect hidden patterns and correlations in data, predicting outcomes, and recommending courses of action for users.

5. Build & Versioning

The build process and versioning are critical aspects of enterprise software development, as they ensure that the software is built correctly, tested, and deployed to production in a controlled and consistent manner.

Automate & document changes to each version of the software, including bug fixes, feature enhancements, and performance improvements. By automated build processes, it is easier to communicate version changes to stakeholders, such as customers, support staff, and development teams, to ensure that everyone is aware of the changes and their impact.

Prioritizing the important features for business and doing away with unnecessary code bloat is an integral part of enterprise software development. By using a version control system, you can track changes to the code, feature enhancements, improvements and manage different versions of the software.

Companies need to use continuous integration and continuous deployment, to ensure that software changes are tested, deployed, and monitored in a controlled and consistent manner throughout application lifecycle. Any enterprise software failure shouldn’t leave the data or the application in an indeterministic state. The build and versioning system should be capable of restoring the system to a failsafe and graceful exit.

6. Ongoing Maintenance & Development

A maintenance & development roadmap is a plan that outlines the steps to maintain and update an enterprise application over time. The enterprise applications are dynamic in nature and change as frequently as the business does.

Conduct a thorough assessment of the application to identify potential areas for improvement, such as performance, security, feature enhancements and user experience etc. Customers using their products may have problems with it or don’t know how to use certain features, so it’s always a good thing to keep all your customer support channels open in this stage. Keep the application up-to-date with the latest technologies, data & security standards etc.

With well defined goals and business priorities, each maintenance task, such as improving performance, increasing security, reducing process time or enhancing the user experience can be implemented. The timeline and budget for ongoing tasks can be undertaken as per business objectives. Companies can use application modernisation to support future business growth and changes, and by using modular, reusable components.

7. Evaluation of Enterprise Application

The performance of the enterprise application can be determined by assessing whether it effectively meets the goals of the organization, its customers and users. This can be evaluated through various metrics, such as user adoption rate, productivity improvements, reduction in errors, reduction in process times, cost savings, customer satisfaction, and other key performance indicators.

User feedback and input can also provide valuable insights into the application’s usefulness and potential areas for ongoing improvement. The effectiveness of enterprise application can be monitored overtime to identify areas for improvement and to ensure that the application is meeting the required quality standards.

Ultimately, the value added for a business is best described in terms of the cost savings, revenue generation and financial impact of the application on the business.

Kreyon Systems is an enterprise software development company using latest technologies to develop high end solutions for clients. If you have any questions for us, please get in touch with us.

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The API management involves defining API policy and release management. Typically, web APIs are used for integration across applications and it may involve using & sharing APIs with third parties too. The APIs can be classified and released as:

i) Private:
The APIs could be used only within the organisation and internal applications. No third party application or company will have access to these APIs.

ii) Partner:
These are the APIs reserved for the partner businesses & applications. These are restricted for common users, but could be availed through exclusive memberships or payments. The Google APIs provides subscription based services for Google Maps for its partners. These APIs provides routes, directions and information at a premium price for partners like Uber.

iii) Public
The public APIs are available for all users. The Google map requests for mobile apps is available for public use. Apple also provides its APIs for programmers. The payments apps like Venmo, Stripe, Visa provide APIs for applications to receive and make payments.

3. Consumers & End Applications

The APIs are typically created for application integrations, there are applications that consume APIs. The clients that consume APIs could be internal to the organisation or third party. However, the end user scenarios and requirements of the consumer applications must be met with APIs.

The APIs can be managed according to the services provided to the consumer application and diverse use cases. API management may involve building connected platforms, structuring information assets for reuse and plan adaptive integration.

4. Next Generation Devices 

While organisations have been building APIs for different client applications and mobile devices, there are new objects getting connected to the internet everyday. These objects and devices will be leveraging APIs. For e.g. Alexa, Google Home, and smart watches are some of the devices that will use the APIs. These devices are part of the ecosystem today and connect with users in novel ways.

The APIs are very much part and parcel of building an internet of things infrastructure. Whether it is your IP cameras, microphones, servers or applications, APIs can leverage two way communication with them. The APIs are powering the digital strategy for the next generation devices and connectivity.

5. Security & Access Management

When everything is interconnected, there are endless endpoints using data and many of them are at a risk of being exposed to malicious users on the web. The API management involves securing access to the data with authentication, authorisation and best practices for security management.

The information security from malicious users and third party apps is the prerogative of the API management. It must guard against rogue applications & users to circumvent any security issues. The API management may also involve a policy check for identity checks on connected devices and applications.

6. Scalable Microservices 

SaaS applications are typically built for scale and reaching out to a massive number of users. The architecture of the application plays a huge role in scalability. The microservices are architectural components that separate parts of an application into small and self containing services. These services can be called with the APIs and can be used for serving a large number of requests. An API can also involve calling one or more microservices to provide data to the client request.

Microservices are lightweight and deployable services that can be used for building individual parts of the application, it creates a base for building scalable web apps. The APIs and microservices are quintessential in creating performance driven applications on the web.

7. API Usage Metrics

The modern day enterprises rely heavily on APIs for their day to day work. In most cases, the companies consume more APIs than it provides. The detailed API usage metrics can break down the usage of external APIs, data and third party details. This API catalogue can also enlist all vendors, clients and partners for organisation’s APIs. The data footprint and users etc can also be tracked.

The API usage monitoring can help companies to plan building more robust and secured platforms. Any anomalous uses of data etc. can be mitigated and reported proactively to the senior management. The API policy can also disable third party applications and clients that breach the rules for consumption limits etc.

8. Development Friendly

APIs make the management of applications easier and development friendly. With the plethora of applications and use cases, businesses are looking to experiment quickly and build novel capabilities all the time. All companies are looking to augment their digital strategies with new tools and apps to make their business consumer friendly.

The API management can make applications decentralised and makes team work independently. With a microservices based architecture, it helps organisations to build separate services without affecting other teams. This loosely coupled architecture can help companies to have small teams to build services for clients. For e.g. an ecommerce company can have a separate recommendations microservice, this microservice may be deployed independently and doesn’t affect other components of the main application.

API management will be integral to how companies manage their data and provide access to other applications in an interoperable world. API management can make businesses more agile, adaptive and drive operations with interdependent applications. 

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An ERP report by Panorama Consulting revealed that after ERP implementation, 49% of organisations said they improved all business processes. Only 5% of businesses said they did not improve business processes. An integrated software for running a company is becoming a basic necessity in the digital age today.

The employees prefer to work for companies that have the freedom to work from anywhere and clients need access to data at all times. An ERP software can integrate all business processes, clients, vendors, human resources, manufacturing of products/services, manage supply chain and accounting & finances in a single system. The cloud ERP makes it easy to make the data accessible from any location.

The report revealed that the top two problems noted during implementation were inadequate testing and inadequate business process reengineering. While 95% of the businesses saw business process improvement after ERP implementation. Most companies benefit from an ERP software, however, not all organisations need it. If you are a start-up with meagre resources, spending on ERP may not be an urgent priority. Here’s a look at some of the tell tell signs that your company needs an ERP:

1. Tedious Excel Sheets & Google Docs

Is your company relying on tedious excels and Google sheets for processes? Are you relying on it for employee updates, leaves, salary etc? How are your vendor/customer relationships managed? Many companies use excel sheets for reporting and data purposes. They even make their employees fill up tedious excels that result in waste of time and valuable resources.

An ERP system can streamline processes for various business functions and provide smooth operational structures. The reporting, communication and overall business processes can be managed using an ERP. The system can also integrate business hierarchies, departments and data into a single software to provide all relevant information to all concerned.

2. No Integrated System for Data

Relying on different sources of data & various applications can be messy. Many times, when there is failure to integrate information, it can lead to duplication of efforts. There are redundancies, out of date information, incomplete integration of systems leading to communication issues and ultimately no single source of truth for the organisation.

An ERP system is the best bet for an organisation to streamline its data. By integrating legacy components and other applications, the ERP can provide all the information needed to run an organisation better.

3. Customized Reports

When organisations use different systems, finding the right reports can be a bit cumbersome. Managing various departments, employees and business functions can be chaotic. The excels and documents may fail to capture the specifics of business processes as per the company needs.

With an ERP system, the company can create customised reports, configure dashboards as per the employee roles and departments, it can also provide timely insights for important actions. The reports can be customized and scheduled as per the needs of the company with an ERP software.

The ERP software can create customised reports with web data connectors across different applications, integrate with Google docs, excels etc. The ERP system can be used for cleaning up, structuring & presenting data as per the business needs.

4. Business Coordination

Is your business relying on too many tools and technologies for operations? Are your day to day needs getting more complex due to disparate tools for communication? How do you stay on top of the data from every department, employee, vendors, inventory & customers? 

With ERP, the complete supply chain of your business efficiently, process times can be improved and data can be centralised leading to better outcomes for your company. Right from the time, a product or service is manufactured to the time it reaches the customer, everything can be streamlined with an ERP. The after sales support, coordination with vendors and managing complete business operations can be done seamlessly with an ERP.

5. Too Many Software & Apps

Many companies find it hard to integrate information across various software applications. They use different systems and best of breed applications, but sometimes integrated views of business is hard to achieve for them. The businesses also feel overwhelmed to manage the complex user based licensing procurement from different vendors. A CRM from one vendor, support system from another vendor & then accounting/finance application from a different vendor, and then legacy data in old applications can lead to integration issues.

Your ERP system can manage all the business processes and also the integrations with ease. It can provide the comprehensive functionality and the customisations needed to address issues for your business.

6. Working Capital & Finance

When a company is operating without a centralised system and control, it can often lead to leakage of capital. Take for e.g. an average company spends a significant amount of money to cover its regulatory compliances. Many of these companies also spend money on penalties, inefficiencies & redundancies. But with an ERP, the organisation can have access to a centralised accounting system. The working capital needs of a company can be regulated and optimised with an ERP system.

Compliance and regulatory reporting is a critical business function for companies. An ERP creates standardized processes for employees, vendors, customers, accounting, regulatory and compliance reporting. The company can enforce budgets and stricter controls with respect to finances for improved bottom line results. 

7. Company Growth & Performance

Are your business processes optimised for best performance? How do you measure the performance of your organisation? Is your company looking for growth? Do you want to ensure standard processes across business functions and locations? Many times, when a company is growing, it leads to chaos, mismanagement and regulatory hurdles. ERP can solve this.

As per the ERP Report, 64% companies opt for an ERP implementation for improving their business performance. They want to position their company for growth and improved performance. An ERP gives a balanced view of the business data and projections for the future. It leads to better planning, coordination, communication and improved performance across the company. 

The ERP implementation can be complex for companies that need a very high level of customisations, causing longer implementation cycles & higher budgets. But, over 91% of companies don’t need a lot of customisations and can use ERP systems without significant changes leading to improved business performance.

Kreyon Systems is a leading ERP Software implementation partner for companies. If you have any queries for us or need help in implementation of ERP Software, please reach out to us.

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We are entering a new era of computing where the world will be driven by machines. The promise of Artificial intelligence is already causing the leading companies and governments around the world to take serious note of it. The modern AI solutions are capable of self learning and evolving with exposure to data. AI is driving whole range of applications from digital assistants, enterprise software, search engines to self driving cars. Here we explore some of the ways in which AI is changing software development:

1. Real-time Data Science :

The amount of data generated by digital systems is enormous. When it comes to enterprise decisions, the right data insights are vital. The AI driven systems are capable of handing large amounts of structured and unstructured data from various sources, interpret them and present them in business context. For e.g. pricing for retail products on ecommerce portals analyses data from the web, demand of products and accordingly increases or decreases pricing for products.

2. Self-taught Algorithms and Analytical tools :

One of the most important facets of an AI system is self learning. The system is developed to learn and improve its capabilities over a period of time. These self taught systems provide insights and actions in context of business events for organisations. For e.g. purchase predictions for online stores, e-coupons to consumers are created using predictive algorithms that use data insights from their users.

3. Virtual Assistants :

The virtual assistants and chat bot applications are now becoming a common place for getting routine tasks done. Google Now, Siri, Alexa and Cortana are quite popular virtual assistants that can help you to order a pizza from your favorite store, book air tickets, get recommendations on a trip abroad and organize your day to day tasks.

4. Automated Customer Service and Interactions :

With the proliferation of chatbots, companies are now adopting them for interactions with customers. These chatbots are built with AI and are learning as per the new data inputs. These chatbots are improving with human like and intuitive interactions with customers. The time to resolve and address customer queries is improving with these chatbots. These chatbots are quite efficient and replacing human agents for routine customer support tasks.

5. AI Driven Applications :

Artificial intelligence has revolutionized the way applications are developed. Ride sharing apps like Uber, Lyft etc are powered using machine learning and AI. These apps make use of AI to come up with the best price for your rides, choose optimal routes for picking up co passengers and minimize waiting time. The applications are developed to solve real world problems. These apps are built using machine learning algorithms that learn with data and this learning is available for all the users.

6. Predictive Automation and Decision making :

Making the right decisions requires evaluation of exponential possibilities today. The data points are spread across various systems and locations. The AI applications are helping companies to automate their workflows, integrate various sources of data and analyze data in context of business events. For e.g. discount on particular market locations and its impact on business, recommendations for improved profitability etc. The recommendations made from the software consider exhaustive combinations in line with the business priorities. The system is constantly detecting the data patterns and makes proactive suggestions to assist decision making.

7. Search & Web :

The search engines especially Google use AI to understand the intent behind the search query. Searching information on the web in context of users need is an area where AI is playing a major role now. The idea of AI based search engine is one that can constantly update itself and produce better results to user queries. The web is also undergoing changes with AI powering many of these. The prominent ones among them are the way online sites make product recommendations, adjust pricing for items, and use realtime data from the social networking sites for marketing.

AI software development is causing major upheavals in the world. The extent to which AI systems take control of human lives remains to be seen. But their impact will be quite significant for sure. The role of AI will be prominent in shaping the future driven by a fusion of digital and physical world. Enterprises around the world are now bracing themselves for AI to achieve new levels of performance at greater scale, growth and speed than ever before.

Kreyon Systems is an AI software development company building multi-tenant cloud based platforms for enterprise software. If you need any assistance on AI based software development, please get in touch with us.

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We live in a mobile economy today. When it comes to booking a taxi, hotel room or buying things, mobile app is now the preferred medium for the users. Users are addicted to their smart phones & apps are a great way to tap into these users. Enterprises are now battling to woo their customers with customised apps. The customised apps are not only geared to simplify process flow for customers, but also act as marketing & branding tools for companies. The following points are an indicative checklist or pointers to help companies plan their mobile app development:

1. Use Case : Companies must figure out a compelling use case for the app. What is the purpose of the app? What needs to be accomplished with the app? Is the app going to be used for fun, sharing information, gathering feedback or achieving a specific functionality? Who are the end users of the app? How are they going to register on the app? Answering these questions will clarify the objectives and goals of the mobile app.

2. Data : While the app is being conceptualised, the data usage patterns also need careful attention. Where will the app get the data from? Does it need to be integrated with an existing Database through APIs, services or external source of data? How will the app data be stored on the server? Understanding these things is critical to design the right architecture for the app.

3. Screenshots : The deliverables for the app must be specific. It is helpful to have the screenshots or mock-ups of the app at an early stage. The screenshots can be evaluated by the key stakeholders and based on their inputs, the app screenshots & workflow can be finalised. One needs to answer the following questions regarding the app: How many screens will be involved? How many users will use the app? What screen resolutions will the app target? Are the main flows & processes in the application covered with the screenshots? The best apps tend to focus on core functionality & eliminate unnecessary features & functionality.

4. Offline Content : Some apps require content to be accessed in offline mode. This means that the app should work even when there is no internet connectivity. This requires storing Data base locally on the mobile. While architecting the solution, it is critical to evaluate whether the app requires data in the offline mode?

5. Platform Support : Developing a native app on all platforms can be a bit tricky for companies. To launch native apps, companies can prioritise the platforms according to the usage patterns of their users.  Does the app need to be supported on iOS, Android, Windows or other platforms? Which platform should be prioritised for development? How will the native platform apps be maintained? These are some of the crucial things that need to be addressed before deciding on the platform support for the app.

6. Notifications, Updates & Features : The functional requirements for the app must be covered with the features. The mode of communication with the end users with notifications, interactivity support and updations must be planned. Companies want to keep engagement levels of their users high with frequent & relevant updates to the app. What type of notifications should be sent to the users? How frequently the app will be updated? What are the context specific actions that the app should take? How will the app be deployed? These are some questions that need to be answered when the app is created.

7. Security : Organisations are wary of storing their sensitive data remotely. The use case for the app will vary from organisation to organisation. What level of security is required for the app needs to be ascertained? How will sensitive data be stored & protected? Will there be any third party integrations required etc? Evaluation of security parameters around important data should be planned to avoid any breaches or loopholes.

8. Special features for Ecommerce/In-app purchase : When the app requires in-app purchase or commercial transactions, comprehensive efforts need to track everything in minute details. For e.g. all product bookings using the app must be traceable from the super-admin panel of the organisation. All bookings, cancellations, user details etc must be mapped with precise details. The app can also be used to collect user information, geo-location details, etc. This may be used by the companies for sending push notifications. It is important to establish, does the app require payment gateway? Is the app designed to support ecommerce transactions? How will the super-admin panel be managed to run the app or the platform etc?

9. Device Compatibility, Data flow & Integrations : Designing an app to meet core functionalities requires that app connects to data from many existing back-end systems. The app should be able to leverage the existing ERP, CRM systems for data access. The app should be designed so that it synchronises data between multiple devices, platforms and systems effortlessly for the end user. The following are some questions that need to be evaluated before an app solution is finalised: What kind of existing systems are used by the organisation? How can the app securely connect to legacy systems? How will the data synchronisation be achieved across devices? Will there be any data migration required for the app?

10. Reports, Analytics & Dashboard : The app can be used to collect user information, usage statistics, and other relevant details. The total number of app users and statistics related to them can be published to the super admin interface. The reports, data analytics & other information can be used for making informed decisions for the company. One needs to evaluate things like, which metrics will be used to measure user engagement? Which key result areas need to be captured for the reports? What is the volume of users for the app? What is the user feedback etc?

Progressive web apps have emerged as a strong alternative to native mobile apps. In most enterprise application scenarios, a progressive web app is able to provide an integrated solution for all platforms. Kreyon Systems is an enterprise software company for ERP Software development, CRM development services & business process automation. Please reach us for any queries or assistance.

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Enterprise resource planning software is an integral need for business today. This infographic illustrates how an ERP software can make business management seamless with automation of the key functionalities. Kreyon Systems is an ERP software company providing ERP implementation with automation of sales management, employee management, HR & payroll software, CRM, accounting, quotations, invoicing, orders, material management, project management, inventory automation, document management & custom modules. If you need any assistance, please contact us.

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