Congratulations to the 2023 APAC Innovation Award Winners

Sahir Azam
March 30, 2023 | Updated: April 4, 2023

I’m thrilled to announce the nine winners of the 2023 MongoDB APAC Innovation Awards. The MongoDB Innovation Awards honor projects and people who dream big. They celebrate the groundbreaking use of data to build compelling applications and the creativity of professionals expanding the limits of technology with MongoDB. This year, we have broken the awards down regionally to celebrate organizations in APAC, from startups to industry-leading enterprises, across a wide variety of industries, who are delivering big results. We are delighted to announce the winners below:

2023 MongoDB APAC Innovation Award Winners:

Positive Impact
Open Government Products

Open Government Products (OGP) is an in-house team of engineers, designers, and product managers, who is a part of the Singapore Government, and is responsible for building technologies for the public good. OGP used MongoDB’s developer data platform, MongoDB Atlas to create its digital form builder, FormSG. Used by the Singapore government and public healthcare institutions, FormSG securely collects data from residents and businesses and helps public officers to create digital government forms in minutes. It eliminates the use of paper forms and the manual process of transcribing physical documents, which had raised concerns around data privacy and protection. During the pandemic, FormSG enabled public officers to collect more than 100,000 daily temperature declarations nationwide. Today, FormSG has served more than 120,000 public officers from 155 agencies and it has created more than 500,000 digital forms to help the government collect data on travel and health declarations by visitors to the country, applications for COVID-19 swab tests, and applications for financial assistance.

Organization Transformation
Bendigo and Adelaide Bank

Bendigo and Adelaide Bank is one of Australia’s largest banks, with around 7,000 employees helping more than 2.2 million customers achieve their financial goals. The bank has been on a multi-year journey of transformation using MongoDB's developer data platform to improve efficiency and deliver a better customer experience as they fulfill their vision to become Australia’s bank of choice.

Recently, the cloud team launched Ready-Set-MongoDB (or RSM). This event-driven framework allows developers to streamline the consumption of internal or external APIs, and applies data transformations and storage automatically within a MongoDB collection of their choice. Using MongoDB Atlas Search, the bank also enabled developers to gain insights across its multi-cloud deployments, identifying cost savings, and providing inventory information to account owners and technical stakeholders.

Within the first 18 months of launching these programmes, the automation had saved the organization more than 1,100 developers days. It also helped reduce human involvement, removed stale data, and allowed engineers to focus on the things that matter. The development of Ready-Set-MongoDB is ongoing and improving, as new Bendigo multi-cloud challenges arise and new MongoDB products are released. The application is a perfect representation of how Bendigo's Technology Department is using modern technology, rapid development, and innovation-led problem solving to drive organizational transformation.

Heroes in Health
Redcliffe Lifetech Private Limited

Over the last few years, Redcliffe Labs has become India's fastest growing technology-driven diagnostics service provider. Redcliffe Labs is on a mission to serve 500 Million Indians by 2030 with fusion of technology and world- class laboratories. The company already serves thousands of people daily, with more than 73 labs and close to 1500 walk-in centers across 180 cities.

Redcliffe Labs has relied on MongoDB Atlas’ flexible document model to power its innovative Smart Health Report, a patient resource that provides a number of indicators and trackers to gauge holistic health. The MongoDB developer data platform's best in class security, compliance, and privacy controls allows Redcliffe's team to confidently handle even the most sensitive patient data.

MongoDB Atlas takes care of many of the traditional database management challenges, which means that developers can spend their time building diagnostics for patients, rather than managing databases. Redcliffe Labs is focusing on incorporating next-generation technologies in the diagnostics space with an AI platform that will make Interactive Diagnostics reports, Advanced Health Profiling and more detailed Diagnostics and Health Alerts.

Industry Disruptor
Cathay Pacific

Cathay Pacific, Hong Kong’s home carrier operating in more than 60 destinations worldwide, has been on an impressive journey to become one of the very first airlines to create a truly paperless flight deck. Until recently, a flight from Hong Kong to New York would require a crew to review more than 150 pages of finely printed text and charts before their flight and make ongoing updates throughout the trip.

In 2019, Cathay Pacific conducted the first zero paper flight, removing 50kg of manuals, charts, maps, and flight briefing paperwork. They achieved this enormous feat with the help of one seamless and highly customized iPad application: Flight Folder. Built on MongoDB Atlas, Flight Folder is designed to improve the pilot briefing experience. MongoDB helped consolidate dozens of different information sources into one place, and made it possible for flight crews to easily share their experiences with others. It also included a digital refueling feature that helps crews become much more efficient with fueling strategies – saving significant flight time and costs. The use of MongoDB Device Sync enables seamless syncing and no data loss even when the app goes on- and offline mid-flight.

Since the Flight Folder launch, Cathay Pacific has completed more than 340,000 flights with full digital integration in the flight deck. In addition to the greatly improved flight crew experience, flight times have been reduced, and digital refueling saves eight minutes of ground time on average. All these efficiencies have helped the company avoid the release of 15,000 tons of carbon.

From Batch to Real-Time
Adani Digital Labs

Adani Digital Labs is the India-based digital innovation arm of the larger Adani group. The lab’s team's mission is to create one single platform – a SuperApp called AdaniOne – to empower a billion stories in India.

To address several use cases and the huge scale that will be required by the superapp, the Adani Digital team selected MongoDB Atlas as its the main transactional database that will further enhance the application.

A key component of the app is how it can bring together disparate data in order to provide a single view of activity across the application. In the first process, developers had taken out the data in batches and sent it to their database However, this was too slow and unpredictable as far as business requirements are concerned. Also, the consolidated view of customer history, orders, inventory, and supply chain network updates was likely to impact their customer's ability to generate revenue.

Therefore, in order to find a better solution, Adani Digital Labs built a more modern architecture in line with MongoDB. Using MongoDB's Change Streams and the data platform's native Kafka connector, they created an event-based architecture that pushes the data out in real-time for analysis. Adani Digital Labs is still in the early phases of the SuperApp's rollout and collaborating with MongoDB as its developer data platform continues to help the firm to grow and deliver insights in real time.

Industry 4.0
Dongwha

Founded in 1948, the Dongwha Group has evolved from a singular focus on the wood and timber industry into a global leader across a number of sectors including building materials, chemicals and media.

As part of its wider digital transformation strategy, Dongwha required smarter factories that would improve and optimize their production efficiency. Dongwha built an innovative Smart Factory Software platform that collects and analyzes data to enhance quality and production management capabilities.

Originally, the platform was built with the community version of MongoDB. However, in order to scale and adapt, the team recently migrated to MongoDB Atlas in the cloud. This enabled them to store large volumes in the fastest and most secure way, optimize their solution for time series data, and make it easy to run machine learning across their data.

Dongwha completed the migration seamlessly, without any disruption or downtime to their factories, and it has now been launched across five different sites. Over the last year, the application has significantly increased its availability and reliability while performance has improved by as much as 6x . As they look to the future, Dongwha plans to roll out the software to more of its international factories.

Digital Native
myBillBook

India is home to more than 60 million small and medium-sized businesses (SMBs) but only a small portion of those SMBs are taking advantage of digitization and many still operate using pen and paper. In addition, many businesses in India still struggle with fluctuations in internet services, outages, and latency. FloBiz is on a mission to change that with myBillBook, a one-stop solution that helps SMBs create professional invoices, manage stock, collect payments, automate reminders through smart banking, engage with their customers, manage staff attendance and payroll and generate more than 25 business reports for accounting and decision making. The app is also mobile-first, so businesses can access them from their mobile devices and allows users to manage billing and inventory in both online and offline environments.

The myBillbook app is powered by MongoDB Atlas, providing the flexible and scalable foundation for the business to do everything from building new features to performing complex analytical queries. In addition, Realm, MongoDB’s mobile database, with Atlas Device Sync, supports offline usage and automatic syncing with the cloud to ensure there is never data or functionality loss for users due to poor internet connection. Because of its success in supporting customers with business critical operations, more than 6.5 million business owners in India are now using myBillbook for their billing, accounting, collection and business growth.

Customer Focused
KASIKORN Business-Technology Group

Established in 1945, Kasikornbank (KBank) is one of the largest and oldest banks in Thailand. Their mission is to strive towards service excellence and empower every customer’s life and business. One of KBank’s subsidiaries, KASIKORN Business-Technology Group (KBTG), developed a mobile banking application – MAKE by KBank. MongoDB Atlas’ flexibility and ease of development enabled MAKE’s development team to choose the best type of database for its tasks, to automate data tiering with Atlas Online Archive, and to reduce hours spent on operational maintenance. With more time to focus on delivering new innovations to customers, they created unique features like Cloud Pocket which can allocate funds into unlimited customizable pockets for separate usage. They also built Pop Pay, a feature that allows users to easily search for nearby friends and transfer money by clicking their profile picture as well as “Expense Summary" a spending analysis services that helps inform and manage users’ financial habits. As of January 2023, MAKE has acquired more than 1 million users, and increased the number of transactions in MAKE from 900,000 to more than 7.5 million in a span of one year.

Massive Scale
China Mobile

China Mobile provides mobile voice and multimedia services via its nationwide mobile telecommunications network across mainland China and Hong Kong. It is the world's largest mobile network operator by total number of subscribers.

The telecommunications leader is using MongoDB to support one of its largest and most critical push services, which sends out billing details to more than 1 billion users every month. Prior to MongoDB, the tech team relied on Oracle, but as the user numbers increased, performance degraded. Despite large investments, it was still taking too long to do basic requests like finalize and deliver bills to users. In 2019, after comprehensive testing, China Mobile migrated to MongoDB. By taking advantage of MongoDB's native sharding, they were able to improve performance by 80% and go from 50 Oracle machines, to just 12 machines for the same workload. The service now handles all current requirements and is set up to scale with future growth.

With the support of MongoDB, China Mobile is growing steadily,with more than 168 million monthly users and has one of the highest customer satisfaction scores in the China Mobile group.

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Three Ways Retailers Use Search Beyond the Ecommerce Store

When consumers think of retail search, the first thing that comes to mind is typically the search bar of an ecommerce website. This is for a good reason: a Salesforce commerce study shows that 87% of shoppers begin their shopping journey in the search bar, and Forrester has found that as many as 68% of shoppers would not return to a site that provided a poor experience. But retailers that exclusively focus on search capabilities in the context of ecommerce are missing out on huge benefits in customer experience and workforce efficiency. To drive fast application experiences, the querying and indexing of data sets is vitally important, and can be a game changer for easy performance optimization. Let’s explore some of the innovative ways that retailers are using search indexes to super-power their application experiences. Why search is important across retail organizations Large retail data sets, like product and customer data, are used by both customer-facing ecommerce or loyalty applications and internal use cases: inventory management, stock management, customer care, purchasing, supplier and vendor management, marketing and more. Customers using ecommerce search bars typically have an excellent “Google-like” experience with auto-complete, faceting, fuzzy matching, etc., but the retail workforce and back office staff often aren't given the same luxury. These internal teams are trying to work efficiently, but they are stuck using front ends powered by a traditional operational database with no search indexing capabilities. These teams are missing out on a search engine that is optimized for unknown or unpredictable workloads. Search indexing will speed up queries where the input is user-defined or might be searching across multiple fields. Let’s look at a comparison: FIgure 1: Database Query vs. Search Query For these under-served and often overlooked use cases, retailers need a quick and cost-effective solution to adding search, like MongoDB Atlas Search. Adding a search index to an application can be done in minutes, without creating operational complexity. MongoDB manages the spin up and management of the backend Apache Lucene search engine, and the complex data and index synchronization activity. Figure 2: MongoDB Atlas: Integrated database and search The three most common use cases for retail The easy addition of search can optimize application performance and usability in the retail industry in three important areas: In-store workforce applications Back office inventory and assortment Customer servicing Figure 3: Example Search use cases in three retail industry areas In-store workforce applications Speed is important in workforce applications, because these interactions happen in real time. Think of an in-store customer spelling out a name in full at checkout for a grocery purchase to be added to a loyalty account. This could add five minutes to a checkout experience, disincentivizing the customer to engage with the loyalty program. Now imagine that the same checkout attendant can identify the customer by any number of data points, not only loyalty number, but also name, first line of address, email, etc., with faster lookup through auto-complete and fuzzy matching. A retailer that MongoDB works with does this auto-lookup in store with Atlas Search in 200-300 milliseconds for optimum customer satisfaction. Customers and staff also can have difficulty remembering or correctly identifying products. A DIY amateur or a new employee can’t be expected to know the exact name or product ID. This is a great use case for search indexing as we do not know the field in the document or the product attribute that we are querying against. MongoDB has customers that stock more than 150 million products. Strong typo tolerance makes life easier for everyone. Back-office inventory and assortment Flawless purchasing and stock management ensures brick and mortar and online stores get the right inventory at the right time to maximize sales and reduce wastage or deadstock. An operator responsible for distributing products into categories will define in which store shelf a product needs to be and adjust this depending on customer behavior and contractual changes with the supplier. Inventory applications will be used on a daily basis by every operator. These are small internal applications that can have a huge impact on the overall business, but are often overlooked by large IT programs for budget or have a smaller IT team. These teams are adopting Atlas Search because they can get it up and running in as few as three weeks and fully integrated into their application without taking on more operational overhead. Customer servicing Long call center or chat conversations wait times have high operational costs and cause customer churn. It is vital to identify the customer as quickly as possible by the data they provide: order or customer ID, phone number, store address, etc. Retailers who have created a “Customer 360” across their customer relationship management and loyalty systems have created a large complex pool of data. The ability to run a single query to search across all available attributes makes it much faster to identify a customer. Search can also be used to optimize speed and accuracy of results for chat applications and chat bots who have to answer a large volume and variety of questions. This is a perfect use case for search with unpredictable user inputs. If answers to the questions can be searched across the entire knowledge base, speed and relevancy can be improved. MongoDB has retailer customers building chatbot applications for internal use cases like an IT team answering common questions, and external ones. For example, on the ecommerce homepage, a chatbot needs search functionality to be able to quickly do product lookup, customer identification, or make a suggestion. Quick and easy search implementation will add to the customer experience and reduce staff operations. Where your company could add search functionality It’s time to think beyond the ecommerce search bar. What are the search workloads within your company’s retail estate? Are there internal applications that have your frontline or back-office staff frustrated with inefficient lookups? Is the reason you’re not implementing search today the fact that it's a heavy lift to add an additional technical component to your architecture? These are the types of conversations that are driving adoption of Atlas Search across the retail industry, as businesses persevere in a tough macro-economic climate to do more with less. Adding vital functionality to applications without adding complexity is a win for the retailer, the workforce and the consumer. Want to learn about how MongoDB has integrated Search into the Atlas Developer Data Platform? Head to the Search solution page to explore more technical and in-depth resources.

March 29, 2023
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MongoDB: Powering Digital Natives

Today's rapidly evolving digital landscape is dominated by digital native companies, driving innovation . These are companies born in the digital age and who operate through digital channels with a business model enabled by technology and data. They are not only adept at using technology but are also reshaping the way software is developed and deployed. This article delves into the challenges and opportunities facing digital natives in modern application development, with a particular focus on the complexities of managing data. We’ll explore how the right data platform can empower your digital native organization to build high-quality software faster, adapt to changing market demands, and unlock the full potential of your business. Strong foundations: The four pillars of tech-fueled growth for digital natives Achieving explosive growth requires a strong foundation built on specific principles, which empower rapid scaling and success. Here, we explore the four key pillars that fuel tech-driven growth for digital natives: Product-market fit, fast: As a digital native, you must continuously ship and iterate products to achieve a quick product-market fit. This builds customer trust and captures opportunities before competitors can in an evolving market. Data and AI-driven decisions: You must leverage data to personalize experiences, automate processes, and guide product decisions. A robust data architecture feeds real-time data into AI models, enabling data-driven decisions organization-wide. Balance of freedom and control: Your developers must have the freedom to choose technologies, even as your organization maintains control over the infrastructure to manage risks and costs at scale. Selected technologies must integrate within your overall technology estate. Extensible and open technologies: You must explore disruptive technologies while maintaining existing systems. Freedom from platform and vendor lock-in enables quick adoption of innovations, from current generative AI capabilities to future technological advances. Data: The unsolved challenge in modern application development From cloud platforms and managed services to gen AI code assistants, advancements have transformed how engineering teams build, ship, and run applications: Agile methods and programmatic APIs streamline development, while CI/CD and infrastructure as code automate processes. Containerization, microservices, and serverless architectures enable modularity, while new languages and frameworks boost capabilities. Enhanced logging and monitoring tools provide deep application health insights. Figure 1: Tools and processes to maximize velocity. But none of these advancements address where developers spend most of their time— data . In fact, 73% of developers share time and again that working with data is the hardest part of building an application or feature. So why is data the problem? Traditionally, selecting a database, often an open-source relational one, is the first step in development. However, these databases can struggle with the characteristics of modern data: it’s high volume, unstructured, and constantly evolving. As applications mature and their data demands grow, development teams may encounter challenges with achieving scalability and maintaining service resilience. Some teams turn to NoSQL databases, but even then they find there are limited capabilities, pushing them back to relational databases. As the application gains traction, the business’s appetite for innovation grows, compelling development teams to incorporate an expanding array of database technologies. This results in an architectural sprawl, imposing on teams the challenges of mastering, sustaining, and harmonizing new technologies. Concurrently, the dynamic technology landscape undergoes constant evolution, demanding teams to swiftly adjust. As a result, self-contained, autonomous teams encounter these hurdles recurrently, highlighting the pressing need for streamlined solutions to mitigate complexity and enhance agility. Figure 2: The evolving tech landscape. Data sprawl: A major threat to developer productivity and business agility Data sprawl is slowing everyone down. The more systems we add, the harder it is for developers to keep up. Each new database brings its own unique language, format, and way of working. This creates a huge headache for managing everything—from buying new systems to making sure they all work together securely. It’s a constant battle to keep data accessible, consistent, and backed up across all these different platforms. Figure 3: Teams building on separate stacks leads to data sprawl and manageability issues across the organization It compromises every single one of the four outcomes your technology foundation should be providing, yielding the opposite results: Missed opportunities, lost customers: Fragmented development experiences consume time as engineers struggle with multiple technologies, frameworks, and extract, transform, and load mechanisms for duplicating data between systems. This slows down releases, degrades digital product quality, and impedes engineers from achieving product-market fit and effective competition. Flying blind: With your operational data siloed across multiple systems, you lack the data foundations necessary to use live data in shaping customer experiences or reacting to market changes. This is because you are unable to feed reliable, consistent, real-time data into your AI models to take action within the flow of the application or to provide the business with up-to-the-second visibility into operations. High attrition, high costs: Complex data architecture impacts development team culture, leading to siloed knowledge, inefficient collaboration, and decreased developer satisfaction. This complexity also consumes substantial resources in maintaining existing systems by diverting resources from new projects that are vital for business competition in new markets. Disruption from new technologies: Dependence on any one cloud provider can stifle innovation for development teams by restricting access to the latest technologies. Developers are confined to the tools and services offered by a single provider, hindering their ability to explore and integrate new, potentially more efficient, or advanced technologies. Speed: A unified developer experience for building high-quality software faster In today’s digital world, speed is king. Your customers expect seamless experiences, but clunky applications leave them frustrated. But traditional databases can be a bottleneck, struggling to keep pace with your ever-evolving data and slowing down development. The future of data is here, and it’s flexible: a data platform built for digital natives . It leverages a flexible document model, letting you store and work with your data exactly how you need it. This eliminates rigid structures and complex migrations, freeing your developers to focus on what matters—building amazing applications faster. Flexible document data models empower developers to handle today’s rapidly evolving application data ( 80%+ unstructured) that relational databases struggle with. MongoDB documents are richly typed, boosting developer productivity by eliminating the need for lengthy schema migrations when implementing new features. Developers get to use their preferred tools and languages. Through its drivers and integrations, MongoDB supports all of the most popular programming languages, frameworks, integrated development environments, and AI-code assistance tools. MongoDB scales! It starts small and scales globally. Built for elasticity and horizontal scaling, it handles massive workloads without app changes. Figure 4: A unified developer experience, integrating all necessary data services for building sophisticated modern applications Introducing MongoDB Atlas : a fully-managed cloud database built for the modern developer. It enables the integration of real-time data from devices with AI capabilities (through vector embeddings and large language models ) to personalize user experiences. Stream processing empowers constant data analysis, while in-app analytics provides real-time insights without needing separate data warehouses, all while automatically managing data movement and storage for cost-effectiveness. MongoDB Atlas simplifies database management with the following: Easy deployment via UI, API, CLI, Kubernetes, and infrastructure as code tools. Automated operations for cost-effective performance and real-time monitoring. MongoDB Atlas customer success stories: Development with speed, scale, and efficiency Delivery Hero Delivery Hero, a global leader in online food delivery, leverages MongoDB Atlas to power its rapid service. Founded in 2011, Delivery Hero now serves millions of customers in over 70 countries through brands like PedidosYa, foodpanda, and Glovo. Having replaced its legacy SQL database, Delivery Hero optimized operations and bolstered performance by using MongoDB Atlas. By leveraging MongoDB Atlas Search, Delivery Hero revolutionized its search functionality, ensuring a seamless user experience for its extensive customer base through simplified indexing and real-time data accuracy. MongoDB’s scalability has empowered Delivery Hero to manage over 100 million products in its catalog without encountering latency issues, enabling the company to expand its services while maintaining peak performance. This agility, coupled with MongoDB’s cost-effectiveness, has enabled Delivery Hero to swiftly adapt to evolving customer demands, solidifying its position in the fiercely competitive delivery market. MongoDB Atlas Search was a game changer. We ran a proof of concept and discovered how easy it is to use. We can index in one click, and because it’s a feature of MongoDB, we know data is always up-to-date and accurate. Andrii Hrachov, Principal Software Engineer, Delivery Hero Read the full customer story to learn more. Coinbase Coinbase, a prominent cryptocurrency exchange boasting 245,000 ecosystem partners and managing assets worth $273 billion , trusts MongoDB to handle its extensive data workload. As the company grew, MongoDB scaled seamlessly to accommodate the increased demand. To further improve performance in the fast-paced crypto world, Coinbase partnered with MongoDB to develop a system that significantly accelerated data transfer to reporting tools, reducing processing time from days to a mere 5-6 hours. This near real-time data access enables Coinbase to rapidly analyze trends and make informed decisions, maintaining a competitive edge in the ever-evolving crypto landscape. MongoDB: Your flexible platform for digital growth With MongoDB, you can freely explore, experiment, develop, and deploy according to your digital-native business needs. If you would like to learn more about how MongoDB can empower your digital-native business to conquer market trends, visit: Innovate With AI: The Future Enterprise Application-Driven Intelligence: Defining the Next Wave of Modern Apps AI-Driven Real-Time Pricing with MongoDB and Vertex AI

November 7, 2024