SDKs and APIs – All you need to know to make an informed decision

Building software in the current world requires high-speed development to meet ever-changing business needs. Products and services are delivered incrementally in Agile mode. 

To meet speed and quality requirements a development team will need to identify the following:

  1. Development tools and frameworks that ensure standardization.
  2. Ready made solutions that can be integrated directly or customized to serve their needs.

Thankfully modern development approaches have ready-to-use SDKs and APIs to meet these challenges. Instead of wasting time and resources on researching, developing, and testing, teams can use a plethora of APIs and SDKs with extensive community support.

An SDK is a full-fledged installable library, while APIs are services exposed by a third party or another service, to be communicated with. Both take away the development effort of a module or feature that you might not be ready with.  Depending on the scenario a developer or team will either need an SDK or just an API. Making an informed decision on when to use one over the other is crucial to successful software development. 

To understand this, let us take an example in which we want to build a native health tracking app. The app will have the following features:

  1. Social authentication through Google or Facebook accounts.
  2. Location tracking to figure out distance covered from point A to B as per the user’s activity. It could be cycling or walking.
  3. BMI calculator.
  4. Diet options.

The list can continue, but we do not want to digress from our main intent of understanding SDKs and APIs.

The first thing to consider while building a native mobile app is that there needs to be an Android and an iOS version to serve the majority of users. Whether one should go in for a native or a hybrid app or build the 2 variants using a Cross-Platform approach requires a separate discussion in itself. The starting point for it could be the skills available in-house.

Android app and social authentication implementation

For our scope, let’s just consider the Android app. The official language for building Android apps is Java. Kotlin also has become an official language for Android development and is heavily promoted by Google. C, C++ runs natively on the phone. Then there is LUA which is not supported natively and requires an Android SDK. You can even use C#  depending on your team’s core competency. This will require either Xamarin with Visual studio or Unity. 

We are going to choose Java here.

The best way to get started for a Java developer is to install Android Studio which is an IDE that automatically downloads the Android SDK and emulator.  The Android SDK is a complete set of development, debugging, testing, and build tools, APIs, and documentation. Using the SDK you can generate APKs that can be deployed to different Android-supported devices. The developer just focuses on the language of his choice based on what is supported by the SDK and uses standard code and framework to get the app up and running. 

The next feature to be built is single-sign-on into the app, using a social account. Both Google and Facebook provide client or server-side SDKs to hide the complexity of the actual implementation and enable the integration through popular languages. The developer just rides on the authentication provided by Facebook and Google. Additionally, the user also grants the app the permission to access information or perform operations on either platform based on our need. In our case, we will have to use the Android SDK provided by Facebook and Google.

To sum up, the Android SDK enables the following:

  1. Enables development of the Android app using a language of our choice, Java.
  2. Provides APIs to access location, UI, camera and other native features. 
  3. Enables localization of the app for different languages through the SDK’s framework if required.
  4. The Java code is compiled to an  Android application package along with the required libraries of the SDK

Hence for our health tracking app, we can use the Android SDK for social authentication

Location Tracking Functionality

One of the key features of the app we are trying to build here is to figure out the distance walked or cycled by the user. We can take the route of custom implementation by spending a couple of days or weeks to come up with an algorithm, implementing and finally testing it. A better approach would be to use an out-of-the-box solution such as Google Maps and save on SDLC time and effort.  Google provides both SDK and APIs related to Maps and distance. In our case, we do not really need the entire Google MAP SDK. We can use just the relevant APIs such as the Distance Matrix API.  It gives you the distance and time between one or more endpoints. 

Let’s consider the Javascript implementation of the distance matrix API. The end-point provided looks like this:

https://maps.googleapis.com/maps/api/distancematrix/outputFormat?parameters

Based on the above URL we can glean that an API comprises of the following –

  1. Protocol – SOAP, REST or GraphQL. In our case it is REST. SOAP is the oldest mode of interaction with heavy schemas and data. REST is an architectural style relying on HTTPs GET, POST,PUT and DELETE operations. GraphQL is a query language promoted by Facebook which solves the problem of under-fetching or over-fetching by REST.
  2. URL – as provided by the service provider.
  3. Request Parameters – Either all parameters are mandatory or some are optional. Any service exposing APIs will share the parameters and their structure. In our case for instance – destinations and  origins are required parameters. Mode (bicycling or walking) is an optional parameter. 
  4. API Key – We will need to pass a unique API key that points to our application using the service for authentication and authorization.
  5. Response – The output is either JSON or XML.

An API (Application Programming Interface) enables easy and seamless data transfer between a client application and the server providing the service. There is no installation required, unlike an SDK. The API logic is completely abstracted by the service provider from the client. APIs contribute to a loosely coupled, flexible architecture. Since the API code lies on the server, it’s maintained by the provider. Because of this dependency, we need to ensure that we choose a reliable provider and also keep an eye out for newer versions.

Hence for our health tracking app, we can use the Google Map API for location tracking.

BMI calculator and diet options implementation

This would be either a custom implementation, an API, or SDK. If it’s not available readily as an API or SDK and is required in a number of different health services or products the organization wants to provide, it would be best to expose it as an API for current and future use. 

Diet options clearly are a custom implementation in our scenario.

Differences between SDKs and APIs

APISDK
An API is used to provide a feature by running on a third-party system in a request-response mode.An SDK provides all the tools, libraries, APIs, and documentation necessary to build the application or feature.
APIs run on separate servers (internal or 3rd party) and hence have a continued dependency on the service for reliable operation.SDKs typically run on the same environment and hence have no interdependencies. However, they use the processing power of the existing environment of the application being built.
This just requires a SOAP/REST/GraphQL call to the server end-point with request parameters defined as per the API documentation. This is available in languages supported by the provider which is mostly based on what can run in the environment expected and the popularity of the language. 
For instance, Java, NodeJS, Python, GO, PHP are the usual languages popular with the developer community.
No installation is required. It requires installation and is therefore bulky. Any upgrades will need to be handled at our end. Some SDKs also allow customizations as per our needs.

In a scenario where just a few APIs are required from the entire stack provided by the SDK and these APIs can be independently run, it’s better to opt for the APIs alone.
Error handling is left to the application based on what is thrown back by the server.SDKs lean on the language’s error handling mechanism besides what the server platform returns. Therefore error handling is handled in a more effective way.
Examples – Map Apis, Payment Apis, AdMob API provided by Google.Examples – JAVA SDK, Android SDK, Facebook’s Single Sign-on SDK.

While SDKs are a superset of APIs, used appropriately, they both have many advantages over custom development. 

Advantages of using SDKs and APIs

  1. Fast and easy adoption – A few lines of code and your feature is ready.  The developer can focus on the core business functionalities of the application instead of re-inventing the wheel or working on something that is not our core area of expertise.
  2. Saves time and effort – Ready to use and can be directly plugged into, thereby shortening development cycle.
  3. Language – In the case of SDKs, they usually support all the popular languages that the implementation needs. For APIs you just have to ensure the communication protocol and parameters are as per the requirements.
  4. Support -APIs and SDKs ensure best practices, provide robustness and have community support.
  5. Documentation – APIs and SDKs have good documentation for developers to understand and use. No expertise required other than knowing the language to be implemented in. 
  6. Updated – Newer features keep getting added to the stack by way of versions which the developer if required needs to just update. Mostly backward compatibility is already handled by the service provider.

Disadvantages of using APIs and SDKs

To summarize, whether it’s an API or SDK, it’s better to follow the reviews of the community before making a selection. Things to look out for are known bugs, limitations, and cost.

Trigent provides a number of ready-to-use SDKs and APIs for many domains such as mobile app development, SCM workflows, Logistics, AR/VR development services, enabling you to focus on your core expertise and saving you a lot of time and effort in your development cycles. To know more, please contact us

Quick Wins in Enterprise Digital Transformation (yet often ignored) – Intelligent Automation

The modern workplace is seeing widespread usage of machines and automation. Enterprise digital transformation, Artificial intelligence (AI), and automation are changing the tide for businesses globally. This means a significant change in the work culture as employees will have to acquire new skills and adapt to the advanced capabilities of machines. 

As per a recent study1 involving over 600 business leaders from 13 countries, more than 50 percent of respondents confessed to having already invested over $10 Million in intelligent automation projects. The AI market globally is presently growing at a CAGR of 40%, all set to touch $26.4 Billion by 2023.

AI,  along with robotic process automation (RPA), voice recognition, natural language processing (NLP), and machine learning (ML), is allowing businesses to blend automation with human capabilities successfully to create intelligent working environments. 

Automation is driving agility for businesses giving them the much-needed competitive edge over others with quick decision-making powers. Clearly, decision velocity powered by AI-driven insights gives you data supremacy to lead in a highly volatile market.

Making a case for Intelligent Process Automation (IPA)

When automation meets artificial intelligence, you get intelligent process automation to scale up your business. While it allows you to off-load routine, repetitive tasks, it empowers better guardrails for all your automation initiatives. It takes the uncertainty out of the picture and enables more personalized execution and processes.

Intelligent automation enhances the overall customer experience. The speed of response has often been a critical consideration while evaluating the customer experience. Intelligent automation is helping organizations meet customer expectations with personalization. Through customized offers, services, and content, businesses are acquiring and retaining customers.

What do the right IPA endeavors ensure?

  • Agile services due to a significant reduction in processing time
  • Greater flexibility and scalability for being able to operate round the clock with capabilities to scale up and down as required
  • Improved quality control due to greater traceability of events and instances and checks at different levels
  • Increased savings and productivity due to a high level of automation
  • Clear, actionable insights to predict and improve drivers of performance

While there is unanimous agreement on the benefits of intelligent automation, not everyone has leveraged these benefits across the organization. What you need is an enterprise-wide approach that promotes a new way of working.

Adding intelligence to the digital mix

A highly automated world does not focus on reducing the headcount but increasing its potential to do more in an agile manner to solve the business challenges of tomorrow. It relies on structured and unstructured data the company collects from the public domain and other stakeholders rather than depending on traditional methods.

Intelligent automation compels you to rethink key business processes. The sales and marketing team gets deeper segmentation to target and sell through advanced analytics. Those working to strengthen the supply chain get to improve production and distribution by leveraging technologies like cloud and analytics across the value chain. Planning and development teams, on the other hand, rely on data-driven insights to integrate them into product performance and boost innovation.

Alibaba Group2 is a classic example of what you can achieve with intelligent automation.

After making significant strides in eCommerce and retail, it has further revolutionized its business processes with its ‘Industrial Vision AI‘ solution for manufacturing and production. It allows the company to inspect raw materials thoroughly to detect minute defects, resulting in a 5X increase in production efficiency. Its automated warehouse is managed entirely by robots taking precision and efficiency to a whole new level.

Regardless of your goal, you need to create a strategic roadmap to align it with your business priorities. This is not possible unless you assess your digital maturity.

What is the role of IT in successful IPA transformation?

Intelligent process automation (IPA) is a melting pot of technologies enabling significant gains for businesses worldwide. IPA should not be confused with robotic process automation (RPA) as unlike RPA that performs repetitive, automated tasks based on predefined rules and inputs, IPA can understand the context, learn, and iterate to support informed decision-making using unstructured and structured data.

Those who have been able to get the full value of IPA have been the ones who have put IT leaders at the helm of their IPA endeavors. CIOs need to strengthen their core with IPA programs to support automation.

Here’s what we recommend:

  1. Assess the high-level value potential

You may start with help-desk requests since that’s where a significant amount of incidents originate. While tickets with low difficulty levels are resolved immediately, those with more complexity are often escalated to specialized teams. Determine how many such requests were handled the previous year, and by multiplying them by the average handling time (AHT) required, you can evaluate the value of this whole exercise.

For instance, an organization with a significant number of requests for password reset or access can leverage RPA bots that work across multiple applications via the user interface to automate ticket resolution and free up employee capacity. Reducing resolution times and a drop in costs associated with outsourcing help-desk support will thus improve performance and profits.

The effort required for these activities often varies. Everything needs to be evaluated critically from backups and patching to security audits and upgrades to understand the effort involved and the value you can garner by planning activities for automation.

  1. Identify the use cases best suited for IPA

Let’s consider the same example mentioned above. In order to automate incidents, organizations need to first identify the ones ideal for automation. An organization may be effectively logging incidents in detail, but due to the large numbers and complexities, support teams may not respond quickly and effectively.

AI can make sense of the chaos and understand the reasons behind the alerts. It may be trained to make appropriate recommendations or even make better decisions to ensure suitable responses.

  1. Elevate customer experiences with better service

AI and automation are changing the customer service landscape for every industry, from retail to aviation. Boeing has a fleet of passenger service robots that operate via sensors installed in their bodies. They are doing their best to reduce the manual work of cabin crews. Though experts argue a human perspective is required for these robots to do what humans can.

The key is to understand the power of automation and integrate it seamlessly into processes and workflows to complement human efforts and endeavors perfectly, as we did in the case of one of our clients Surge Transportation.

The company links shippers and carriers and has an automated tracking and monitoring system to assign loads. But the pricing and quotation were being done manually. This drained their resources, led to a huge turnaround time, and left a long log of emails, calls, and paper trails.

Trigent critically evaluated the complexities in its pricing mechanism to bring down the turnaround time to less than a second. Apart from 100% pricing accuracy, the company improved profits by 25%, revenue by 40%, and reduced the load processing time by 91%. With seamless carrier integration, the company now processes 4000 more loads per day.

Other use cases where AI and Automation are driving value

Cashier-less stores

Amazon is popularizing the concept of cashier-less stores with Amazon Go and Just Walk Out. Robotization of stores helps save operational expenses and gives shoppers a smart shopping experience.

Automated medical appointment scheduling

No-shows have been the cause of losses of over $150 billion a year for the U.S. healthcare system with every unused time slot costing individual physicians $200 on an average. No-shows also impact the health of patients since continuity of care is interrupted. IPA challenges traditional scheduling methods by ensuring error-free appointment scheduling based on the nature of the illness, the convenience of patients, and the availability of doctors and healthcare facilities. While patients get to choose a date and time for different health issues, follow-up appointments can be scheduled automatically along with reminders.

Automated supply chains

The ideal supply chain is where there is neither wastage nor out-of-stock scenarios. In tandem with machine learning, AI predicts demand based on location, weather, trends, promotions, and other factors. Revenue losses of up to $4Trillion have been caused due to supply chain disruptions following the pandemic with 33% attributed to commodity pricing fluctuations as per a report.

The automobile giant Toyota is using AI in its manufacturing environment to address waste control with its ability to predict when excess parts, products, and practices threaten to impede work.

Intelligent Automation is clearly the Winner streak!

The potential value of AI and automation is immense for different sectors and will vary depending on the type of industry, availability of abundant and complex data, use cases, and other factors. To get the most out of your automation initiatives, it is however important to tide over organizational challenges with the right mindset and approach.

Create impact and value with Trigent

Trigent with its team of technology experts empowers you to stay relevant and competitive. It is equipped with insights and intelligent solutions to dramatically boost your bottom line and improve customer engagement.

Allow us to help you grow your business and increase revenue with strategies and solutions that are perfect for you.

Call us today for a business consultation

References
1. https://www.analyticsinsight.net/intelligent-automation-accelerating-speed-and-accuracy-in-business-operations/
2. https://datacentremagazine.com/technology-and-ai/alibaba-group-adopts-ai-and-automation-singles-day

AI Implementation Checklist – 5 Points to Evaluate Before Adopting AI in Your Organization

Artificial intelligence is now all around us in household gadgets as well as business workflows. AI adoption is rampant across sectors; the global artificial intelligence market is expected to reach $ 266.92 billion by 20271 at a CAGR of 33.2% during 2019-2027. Nearly half of the respondents who had participated in a survey confessed to being interested in AI implementation and machine learning to improve data quality.

No doubt, artificial intelligence is the proverbial genie that does everything we want it to do without even rubbing the magic lamp. But the lack of nuance and failure to spell out caveats can result in AI systems that will make us think twice before we wish for anything.

Believe it or not, misaligned AI can be a nightmare.

A classic case is YouTube2, with its AI-based content recommendation algorithms that led to users accusing it of radicalization. Its constant upping-the-ante approach led users to extreme content in a bid to maximize viewing time. So videos on vegetarianism led to veganism, and jogging searches resulted in ultramarathons. This unintentional polarizing and radicalizing highlights one significant challenge: we have yet to define the goals accurately for our AI systems!

The sad truth is that we don’t even know what we want, at least not from our autonomous systems and gadgets and other possessions. For instance, a self-driving car may be too slow and brake too often just the way it was designed to prevent itself from colliding with nearby objects. But the object could be as insignificant as a paper bag that was blown away by the wind.

What we need is goal-oriented AI born with a solid sense of purpose with excellent human-machine coordination. But only after you have answered the question- Do I really need AI?

Here’s is your ultimate AI implementation checklist

AI has ample scope in many sectors. AI can interact on your behalf with customers, as in the case of chatbots, or help healthcare providers diagnose cancer and other ailments. If leveraged well, it can help you turn a new leaf in critical interactions with your customers. Understanding the potential of AI and applying it to enhance critical business values can make a world of difference to your business. The key is to know where you stand and whether AI can help you attain your business goals.

Identify the purpose

Organizations with successful AI implementations are usually the ones that have assessed its financial impact or conducted a thorough risk analysis for AI projects. Having the right metrics in place gives you a sneak peek into the risks and benefits of AI implementation and how it would perform in those chosen areas. While it may not guarantee a positive ROI, it gives you a fair idea about what to expect. 

Accuracy, for instance, is an important metric, but it’s not enough to understand how well your AI systems are performing. You need to correlate  AI metrics to business outcomes to ensure you get the most out of your investments. 

The smart pricing tool created by Airbnb to eliminate pricing disparities between black hosts and white hosts presents a classic example. While the AI-based system performed the assigned tasks with precision, the business results fell short – widening the gap further by 20%. 

Appoint mixed-role teams for all AI initiatives

Those who have implemented AI successfully will tell you how crucial it is to build mixed-role teams comprising project managers, strategists, application designers, AI researchers, and data scientists to ensure a diversity of thought and skillsets. As per a Garnet Research Circle survey3, skills are the first barrier to AI adoption, and 56 percent of respondents believed new skills are required for new and existing jobs.

AI needs experts for it to evolve to its best version. TayTweets, a promising chatbot by Microsoft, was nothing but fun, and people loved talking to her. Until, of course, she became the nastiest chatbot ever in less than 24 hours, responding with offensive tweets. It demonstrates how horribly things can go wrong when AI and ML go awry when left unchecked.

Diversity in technical acumen enhances the value of AI to customers since the people working with AI know-how and where it should be used to have the most significant impact. Whether you want to hire new people or train existing ones for newer roles and responsibilities is something you will have to decide based on the business initiatives you have in mind.

Make a business case for AI

Businesses need AI for different reasons ranging from data security and fraud detection to supply chain management and customer support. You need to identify the use cases and applications to determine how AI can be effectively used. Organizations depend on AI to analyze contextual interaction data in real-time and compare it with historical data to get insights and recommendations.

Data plays a pivotal role in every aspect of a business. While a lot of emphases is placed on coding, math, and algorithms, many organizations are not able to apply the data acquired effectively in a business context. You will have to understand who you are building these solutions for and what technology framework you will require to do so.

As Moutusi Sau, principal research analyst at Gartner4, points out, “Business cases for AI projects are complex to develop as the costs and benefits are harder to predict than for most other IT projects. Challenges particular to AI projects include additional layers of complexity, opaqueness, and unpredictability that just aren’t found in other standard technology.”

Assess your AI maturity

It is impossible to arrive at a strategy without evaluating where you stand against the AI maturity model. Once you know it, you can decide the next steps. Typically, the AI maturity model has five levels:

Ø Level 1 – There is awareness in the organization, and AI implementation is being considered, but no concrete steps have been taken in that direction.

Ø Level 2 – AI is actively present in proofs of concept and pilot projects.

Ø Level 3 – AI is operational, and at least one AI project has made its way to production with a dedicated team and budget. 

Ø Level 4 – AI is part of new digital projects, and AI-powered applications are now an essential part of the business ecosystem.

Ø Level 5 – This should be the ultimate goal where AI is now ingrained in the organizational DNA and plays a transformative role for your business. 

Look beyond the hype

AI can cause ‘cultural anxiety’ as a significant shift in thought and behavior is necessary for successful AI adoption. A compelling story to help employees understand how AI would be beneficial to all is necessary to ease the resistance they might feel towards the change.  CIOs should recognize their fears and anxiety of the possibility of being replaced by machines and encourage an open dialogue with team members. This will build trust and help determine if the organization is ready for AI.

The hype around AI itself can sometimes be the biggest problem as organizations hurry to hop onto the AI bandwagon with insufficient understanding of its impact. Explains Whit Andrews, distinguished vice president analyst at Gartner, “AI projects face unique obstacles due to their scope and popularity, misperceptions about their value, the nature of the data they touch, and cultural concerns. To surmount these hurdles, CIOs should set realistic expectations, identify suitable use cases and create new organizational structures.” 

 AI to Impact

The biggest mistake organizations make when they invest in AI is that they have too many expectations and little understanding of AI capabilities. Rather than getting caught in the hype, you have to be realistic and evaluate its role critically in furthering your business objectives.

AI is an expensive investment that will give you good returns if you know how to use it. A lot of tools are good, but not every AI tool is suitable for your business. What you need is the right AI implementation strategy created with professional help from those who know AI like the back of their hand.

Adopt AI with Trigent

Artificial intelligence is a defining technology that can be successfully integrated into business workflows and applications. We at Trigent have been helping organizations from diverse sectors, including healthcare, retail, BFSI, and logistics, create AI operating models that are optimized for faster and effective outcomes. 

We can help you, too, with everything from strategy and implementation to maintenance and support.

Call us today to book a business consultation

References

  1. https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114
  2. https://firstmonday.org/ojs/index.php/fm/article/view/10419/9404
  3. https://www.gartner.com/smarterwithgartner/3-barriers-to-ai-adoption/
  4. https://www.gartner.com/smarterwithgartner/how-to-build-a-business-case-for-artificial-intelligence/

Transportation and Logistics Go Places with RPA at the Helm

Tedious, repetitive tasks can put quite a drain on your time, especially when you would rather spend it on more meaningful activities. Take emails, for instance, you cannot do without them, you cannot ignore them, and there will be quite a few that will require you to prioritize and take action.

Sifting through the entire information to take only the necessary data to the operating system for crafting a response can be overwhelming especially when you would want to focus on important activities such as building relationships with customers or planning for business growth. Thankfully, after a successful run across industries including financial services, healthcare, and hospitality, Robotics Process Automation (RPA) has now made its debut in transportation and logistics.

RPA bots are easy to use and you can integrate them with your existing technology infrastructure even if the systems they work with do not integrate with one another. The fact that the global robotic process automation market size is expected to touch $13.74 billion by 2028 at a CAGR of 32.8% over the forecast period only makes it evident how eager enterprises are to adopt RPA.

Enterprises have always been on the lookout for ways and means to monitor costs and resources. RPA offers them just that, making its way across business departments and processes reducing human error, and amplifying throughput.

Some organizations have been hesitant to adopt RPA because they weren’t sure if their scale could support this technology. The capabilities that RPA brings along are however helping them realize its value and potential. No matter which industry we speak about, transportation and logistics form an integral part of their supply chain. Any improvement in business processes thus has a positive impact on all others.

It’s time we delved deeper into the benefits and use cases that make RPA the smartest solution out there for streamlining processes in transportation and logistics.

The RPA benefits

RPA offers several benefits when you put RPA at the helm of business processes. Jaguar Freight recently announced its decision of choosing RPA Labs for the documentation of its document processes.

Speaking about its decision, Simon Kaye, President, and CEO of Jaguar Freight elaborated, “We recently partnered with RPA Labs, who does a tremendous job automating a lot of the heavy lifting within our organization. They helped us in two areas – one is taking a lot of raw data from client documentation, commercial invoices, and packing lists, and populating that automatically in our system, where previously there was a fair amount of data entry, which caused a lot of errors and delays.”
Not just big enterprises, but even startups are now eagerly embracing the power of RPA to streamline their operations.

Some of the top benefits of leveraging RPA solutions include:

  • Time – Automation has always saved enterprises a lot of time, but RPA tools streamline tasks helping them further bring down the process cycle time significantly.
  • Accuracy – Due to the absence of manual intervention, RPA ensures high accuracy. Tasks performed are usually error-free and in the rare event that an error occurs, it can be found and fixed easily. This is possible because RPA-driven processes are recorded and easily retrieved.
  • Productivity – Higher accuracy ensures better work management. It helps enterprises align processes with their business goals ensuring productivity is at an all-time high.
  • Revenue – With reduced process cycle times and increased accuracy and productivity, enterprises are able to devote their time to grow their business and increase revenue.

To take a closer look at the different processes that benefit from RPA and understand how RPA plays a role in enhancing organizational efficiencies, let’s look at its applications.

Order processing and tracking

The one area that involves endless manual data entries and can improve significantly is order processing and tracking. It’s not just tedious and time-consuming but also very resource-intensive. Manual errors can prove to be extremely costly at this stage. RPA enables organizations to process orders efficiently. PRO numbers of shipments are picked up from a carrier’s website automatically via bots and loads are closed out in no time.

Tracking continues with the help of IoT sensors even after orders are processed and shipped. IoT sensors also ensure that products can be traced based on their last known location in case they get misplaced during transit. The rationale is to keep both employees and customers in the loop so that the status of shipments is known to all concerned at all times.

The RPA tool also sends out updates in the form of emails at regular intervals. This feature comes in handy when the transit period is too long. Customers also get plenty of time to schedule pick-up times based on the location of the product.

Inventory management

Another important task that comes under the domain of RPA in supply chain and logistics is that of inventory monitoring. After all, supply needs to be aligned with the demand for products and the expectations can be met only when you know exactly how many products are left and when new shipments are going to be needed.

RPA tools look into this aspect and send a notification to concerned employees about the number of products remaining and even order new products as required. Supply and demand planning is possible only when you are able to analyze diverse data from suppliers, customers, distributors, and your workforce. RPA can gather, store, and analyze data to help you tide over these challenges and maintain a steady supply.

Invoice management

Like order processing, invoice management also involves entering and processing a huge amount of data. With RPA tools, you can substantially reduce the stress of going through invoice documents and ensure error-free processing. In a typical business scenario in transport and logistics, orders are received, processed, and shipped in large numbers every day.

While it took days in the pre-RPA era to process invoices, RPA ensures that invoices are processed quickly and accurately, extracting only pertinent information to enable automatic payments. This helps businesses reduce the average handling time by 89% with 100% accuracy and achieve a resource utilization of 36%.

Report generation

You need reports for just about everything; be it for processing payments, gathering customer feedback, or managing shipments. When it comes to transportation, report generation assumes a whole new level especially when you are tracking movements from city to city, port to port. Often, it can get tiresome and challenging.

RPA helps you manage all your report-related chores with ease thanks to its ability to screen information. Minus the human intervention, RPA-generated reports are highly accurate. Modern enterprises combine the capabilities of RPA with Artificial Intelligence to generate precise reports and even make sense of them to offer actionable insights.

Communication and customer satisfaction

In a sector as busy and extensive as transportation, communication is the key to better relations and customer satisfaction. Customers need timely updates and the fact that multiple vendors and partners are divided by distance and time zones can sometimes pose challenges in communication. This is where RPA tools such as chatbots and auto-responders come into play.

They communicate, interact, and answer customer queries. They also push notifications as often as required to inform concerned authorities about order status or shipment delays or other related matters. This in turn ensures a high level of customer satisfaction. Given the stiff competition, it is the only way customers are going to keep coming back for more.

While old customers are happy to hang around, new customers will look forward to a long association thanks to RPA-enabled services. The best part about RPA tools is that they allow you to link information across stages and processes to have the right information necessary for providing efficient customer service and 24X7 support.

Take your business to new heights with Trigent

Trigent with its highly experienced team of technology experts is helping enterprises improve process cycle times and create new opportunities for increasing revenue. They can help you too with the right RPA tools and solutions to enhance process efficiencies and create better customer experiences.


Allow us to help you manage your workflows and add value with RPA. Call us today to book a business consultation.

How universities are using AI to power operational efficiency

The role of technology in the education industry has witnessed some monumental trendsetters, right from 2019, which saw the advent of Big Data, Internet of Things (IoT), and Machine Learning. Artificial Intelligence (AI) has also been a significant contributor, revolutionizing education. Keeping up with the changing times, universities have started embracing AI. A Market Search Engine report has predicted that AI will become the primary trend and grow more than 45% by 2024. The pandemic has also proven to be a catalyst for positive change, accelerating universities’ education technology needs.

Artificial intelligence has been in use for quite some time now. Several industries have already leveraged this new-age technology and seen substantial improvements in their processes. The education sector is the latest to join the AI bandwagon. Colleges and universities globally have introduced AI in their instructional and institutional operations. Managing the entire operations—right from student screening to placements—has been an arduous task, but not anymore.

Leveraging the power of AI

AI’s influence across universities

Recent advancements in AI have made the academic world more convenient and personalized. It has not just made education accessible to students but helped universities automate and speed up tedious administrative tasks.

  1. Admissions and student screening: Leveraging cognitive technologies in the admission process helps universities predict the applicants most likely to be accepted and enrolled, their states and countries, courses they choose, and if they’ll become engaged alumni. AI speeds up the admission and administrative processes, including admissions decisions, visa processing in case of an international student, student housing selection, and course registration.

    Taylor University in Upland, Indiana, deployed algorithms to maximize their student recruitment with a competitive skill set.

  2. Round-the-clock query resolution: Educational institutes use chatbots to perform multiple functions, including conversations with students, answering queries besides assessing and correcting assignments. Chatbots also store, process, and communicate data.

    Georgia State University installed ‘Pounce’ to address issues/obstacles faced by students, including enrollment, class registration, placement exams, and financial aid applications. Students connect to the bot through smart-text messaging and resolve their queries 24/7.

  3. Video-assisted remote learning: Overnight, distant learning has become the top trend due to the pandemic, giving rise to online education to help students effectively learn without disruptions. Though AI can never replace a human, video calls for better teacher-student engagement, irrespective of their location. By using AI-enabled Learning Management System (LMS), teachers can monitor student progress. Students are classified based on their learning ability and content designed to suit each learning style. Reading assignments and long lectures can be broken into smaller segments, helping students understand them better. Machine learning, along with text summarization, can transcribe complete lectures. Students can also connect with their peers, exchange notes, and clear doubts, real-time, while teachers can pay attention to students who require personalized coaching.

    Ivy Tech, a community college, having campuses across Indiana, leveraged AI to enable its student base to perform better. An algorithm was developed to monitor students’ online behavior patterns and identify students at risk of failing. Around 3,000 students were assisted, thereby improving their chances of getting better grades.

  4. Immersive content with AR/VR: Virtual experiential learning has pushed the boundaries of traditional education. Immersive technologies like Augmented Reality (AR) and Virtual Reality (VR) provide a digitally constructed environment to enhance the learning experience. Students can perform science experiments, surgeries, or even explore the universe, along with their peers.

    Arizona State University introduced virtual reality (VR) labs for its biology students. They draw blood, analyze samples, manipulate DNA, and perform experiments, all without leaving their study spaces.

  5. Monitoring students’ performance: Machine learning tracks students’ progress and needs individually and provides insights for enhanced outcomes. Teachers can use these insights to better cater to each student’s academic and personal growth.

    Kent State University in Ohio has integrated AI in its developmental math program. With ALEKS (Assessment and Learning in Knowledge Spaces), students take online classes in a monitored classroom, often assisted by a graduate assistant, faculty member, or peer tutor. Based on the student’s understanding, the difficulty of math problems is adjusted.

  6. Placement assistance: AI-powered platforms and digital analytics can help universities to manage placement and alumni efficiently. Conversational AI, powered by human expertise, is integrated to plan on-campus push, campus recruitments, assist students in cracking placement exams, and monitoring their progress.

  7. Automating administrative processes: Administrative tasks, though time-consuming, are a necessary function. Administrators are often overwhelmed with repetitive work such as new student admissions, managing class schedules, student attendance, processing grades, and monitoring placements. Automation is a crucial way to reduce their burden substantially and keep the processes running smoothly. The staff can eliminate manual routines and instead focus on more creative and inventive roles.

    New York University has deployed BobCat, an AI program that maintains the institution’s library. It plays a librarian’s role, helping students and teachers search, scan, and get library resources such as books/ebooks, sound recordings, videos, e-journals, etc. It also keeps track of the repository, maintains check-out and records for all returns.

AI has enhanced the way teachers run their classrooms. It has also helped administrators expedite their tasks. It replaces the traditional pen-and-paper method with innovative teaching methods, collaborative task management, and seamless operations. Recognizing the potential AI brings to the table, universities, in collaboration with IT companies, are deploying intelligent algorithms. These timely interventions are helping universities address challenges and drive efficiency across functions.

Conclusion

Artificial intelligence is undeniably transforming the education sector worldwide, and the potential for progress is tremendous. With artificial intelligence surpassing human abilities and making a difference in the way universities function in more profound ways, it is the right time to jump on the bandwagon. And for that, you need an expert partner.

At Trigent, we provide AI solutions that are easy to use and intuitive, ensuring seamless adoption of this latest technology. With Trigent’s AI-powered tools, you can accelerate your digital transformation initiative in this new normal successfully.

Reach out to us for a business consultation. We’d be happy to partner with you on your AI adoption journey.