Anoop Dhankhar

4 results

Aussie Fintech Monoova Leads the Way on “Multi” “Cloud” (Not “Multi-Cloud”), to Solve Data Security and Compliance Conundrums

Monoova is a fast-growing Australian Fintech scale-up providing real-time payment solutions to businesses. Having grown from 200,000 to 6 million business accounts in 5 years, Monoova has also created 13% of Australia’s PayID since the inception of NPP, and processed over $100 billion in payments. Dealing with critical financial information from hundreds of organisations in highly regulated industries means Monoova needs to put data security and compliance first. But this is easier said than done. Navigating an increasingly complex security and compliance landscape The increased reliance on the cloud, combined with more regulations requiring extra resilience capabilities, means that financial services organisations are facing increasingly complex data security and compliance challenges. APRA’s chair John Lonsdale recently warned the financial sector about cybersecurity non-compliance, mentioning CPS 230 as one of the upcoming regulations organisations should start preparing to comply with ahead of the July 2025 deadline. On November 3rd, 2023, Brad Jones, Assistant Governor of the Reserve Bank of Australia (RBA) gave a speech in which he listed the “Outside Operational Risk (Cloud Concentration Risk)” as one of the main threats to financial stability . “Multi” “cloud” or “multi-cloud”? A significant number of financial services institutions today aren’t using multi-cloud in a way that would make them resilient in the event of a data security or outage issue. Many say that they are using “multi-cloud” but what they are doing is hosting individual workloads and data sets in different clouds, which doesn’t provide full resilience and data security or meet requirements from regulating industry bodies and government. True multi-cloud resilience means having critical data hosted in different clouds at the same time. For Monoova’s CTO, Nicholas Tan, future-proofing compliance and data security lies in adopting a true multi-cloud approach, and this is exactly the path Monoova has taken by working with MongoDB Atlas. “Whether it’s in critical sectors like financial services or telecommunications, time and time again we see events such as outages seriously impact Australian organisations and their sometimes millions of users - the Optus outage from November 2023 is a perfect example," explains Nicholas Tan. “There are great operational risks of not having diversity in an organisations’ core infrastructure, and this is why building real resilience with a proper multi-cloud approach should be a no-brainer.” Working with MongoDB Atlas a game changer MongoDB Atlas, which is the operational database underpinning all of Monoova’s services, was chosen by Monoova to support extra scale requirements as it was - and still is fast growing, as well as empower developer productivity as the company needs to bring new products to market and innovate fast. Another key driver in working with MongoDB Atlas was the unique functionality that enables users to simply “turn a switch on” to automatically enable selected critical data and workloads to go multi-cloud, allowing data to be easily distributed across different clouds and providing resilience and protection for the workload. Tan and his team simply have to choose the UI to reconfigure their posture to be multi-cloud, which takes only a few minutes. Monoova’s MongoDB Atlas multi-cloud console According to Tan: “Our multi-cloud approach is pretty unique in the current Australian financial services landscape, and this is what has set Monoova to be one of the first Australian financial services organisations to align with the CPS230 framework, as well as at the forefront of ensuring compliance and resilience in an environment heavily reliant on third parties.” “Working with MongoDB has been a game changer because it means we were able to quickly scale up at a fraction of the manpower required; it saved us from recruiting a full team if we had had to do all that multi-cloud work in-house.” Learn more about MongoDB Atlas and our multi-cloud feature on our resources page .

February 20, 2024

Safety Champion Builds the Future of Safety Management on MongoDB Atlas, with genAI in Sight

Safety Champion was born in Australia in 2015, out of an RMIT university project aiming to disrupt the safety management industry, still heavily reliant on paper-based processes and lagging in terms of digitisation, and bring it to the cloud. Most companies today need to comply with strict workplace safety policies. This is true for industries reliant on manual workers, such as manufacturing, transport and logistics, construction, and healthcare, but also for companies dealing with digital workers, both working in the office or remotely. To do this, organisations rely on safety management processes and systems that help them comply with government and industry-led regulations, as well as keep their employees safe. Whether it’s legal obligations about safety reporting, management of employees and contractors, or ways to implement company-wide safety programs, Safety Champion’s digital platform provides customers more visibility and tracking over safety programs, and a wealth of data to help make evidence-based safety decisions. "Data is core to our offering, as well as core to how next-generation safety programs are being designed and implemented. With paper-based processes, you simply can’t get access to rich data, connect data sets easily, or uncover organisation-wide insights and patterns that can help drive efficiencies and improve safety outcomes," explains Craig Salter, Founder of Safety Champion. MongoDB Atlas: Unlocking the power of data and analytics to improve safety outcomes for customers Safety Champion started using the self-managed version of MongoDB, and shortly after that in 2017 moved onto MongoDB Atlas which was more cost-effective, meant less overhead and not having to manage the day-to-day tasks required to keep a database up and running. The main challenge is that industry standards and policies around safety vary significantly for every company - the safety risks of an office-based business of digital workers are widely different from the risks workers on a manufacturing plant are exposed to, making data collection and itemisation for deeper insights very complex. MongoDB’s document model, its flexibility, and its ability to handle complex sets of data combined with Atlas’ ease of use for developers made it the perfect fit for Safety Champion. "It was very easy to get started on MongoDB, but also super easy and quick to get applications developed and brought to market," says Sid Jain, Solution Architect for Safety Champion. "The performance optimisation we saw using MongoDB Atlas was significant, and it freed up a lot of time from our developers so they could focus on what matters most to our business, instead of worrying about things like patching, setting up alerts, handling back-ups, and so on." The use of MongoDB Charts also gives Safety Champions’ customers access to important analytics that can be presented in visual forms, fitting very specific use cases and internal audiences. This helps organisations using Safety Champion improve decision-making by presenting very concrete data and graphs that can fuel evidence-based safety decisions. "MongoDB Atlas helps drive efficiencies for our clients, but it also helps safety and operations managers to have a voice in making important safety decisions because they are backed by strong data-led evidence. Connecting data sets means the ability to have a much deeper, richer view of what’s happening and what needs to be done," says Salter. Managing exponential growth: 2024, the year of scaling up, generative AI, Search, and much more Before 2020, Safety Champions was still a small start-up, with its platform managing about 5,000 documents a month - these include incident records, checklists, inspection reports, actionable tasks, task completion reports, and more. The COVID pandemic forced organisations to move their safety processes online and comply with a whole new set of safety measures and policies, which saw the company’s business explode: triple-digit annual growth between 2021 and 2023, a dev team that tripled in size, over 2,000 customers, and now up to 100,000 documents handled per month. "As our company kept growing, with some of our new customers handling tens of thousands of safety documents every month - we knew we needed to enable even more scale and future proof ourselves for the next years to come," explains Salter. "We also knew that if we wanted to take advantage of MongoDB’s capabilities in generative AI, search, multi-region, and more, which a lot of our customers were asking for, we needed to set some strong data foundations." Safety Champion is now in the process of upgrading to MongoDB 6.0, which will offer its clients more speed, especially when handling larger and more complex queries. MongoDB Search is now also available system-wide, allowing search queries to be performed across all the modules a client has added records for. "Since many modules allow linking records to each other, allowing a single search query to find and return records from multiple modules makes a world of difference. Developers no longer have to maintain other data systems and the extraction, transformation, and sync of data between MongoDB and search index happens seamlessly, greatly reducing the Ops burden on dev teams," explains Jain. The use of multi-region functionalities within MongoDB Atlas means customers, especially global ones operating in multiple geographic regions, will be able to segregate data and ensure they meet regulatory requirements around data hosting and security. Lastly, Safety Champion is exploring the potential of generative AI with plans to start using MongoDB Vector Search , later in 2024. Some of the use cases the company is already investigating include semantic insights, understanding textual data that employees enter in forms, applying LLMs to that data, and extracting helpful information from it. "Every client wants more analytics, more insights, and more high-level meaning out of data. It’s not just about making it easier to enter data and seeing safety incidents, it’s about what it means and decisions that can be made from a safety perspective," says Salter. "The new version of the Safety Champion platform powered by MongoDB Atlas means we are fully ready to dive into the next phase of our evolution as a business and offer features such as generative AI which will take both Safety Champions and our customers to the next era of safety management."

February 14, 2024

Spotlight on Two Aussie Start-Ups Building AI Services on MongoDB Atlas

Australian-based Eclipse AI and Pending AI are using the power of MongoDB Atlas to bring their AI ideas to life and blaze new trails in fields including pharmaceutical R&D and customer retention. With the recent advancements in the fields of AI and generative AI, innovation has been unleashed to new heights. Many organisations are taking advantage of technologies such as Natural Language Processing (NLP), Large Language Models (LLMs), and more to create AI-driven products, services, and apps. Amongst those that are blazing new trails in the AI space are two Australian start-ups: Pending AI , which is helping scientists and researchers in the pharmaceutical space improve early research & development stages, and Eclipse AI , a company that unifies and analyses omnichannel voice-of-customer data to give customers actionable intelligence to drive retention. What they have in common is their choice to use MongoDB Atlas . This multi-cloud, developer data platform unifies operational, analytical, and generative AI data services to streamline building AI-enriched applications. Here is how we are helping these two Australian start-ups create the next generation of AI products faster, with less complexity, and without breaking the bank. Pending AI improves pharmaceutical R&D by leveraging next-generation technologies Pending AI has developed a suite of artificial intelligence and quantum mechanics-based capabilities to solve critical problem statements within the earliest stages of pharmaceutical research and development. The Pending AI platform is capable of dramatically improving the efficiency and effectiveness of the compound discovery pipeline, meaning stakeholders can obtain better, commercially viable scaffolds for further clinical development in a fraction of the time and cost. Building its two artificial intelligence-based capabilities - Generative Molecule Designer and Retrosynthesis Engine - was a mammoth task. The known number of pharmacologically relevant molecules in chemical space is exceptionally large, and there are over 50 million known chemical reactions and billions of molecular building blocks - expert scientists have to undergo cost- and time-inefficient trial-and-error processes to design desired molecules and identify optimal synthesis routes to them. Pending AI needed a database that could handle a very large number of records, and be highly performant at that scale, as required by the vastness of chemical space. A few databases were considered by Pending AI, but MongoDB kept standing out as a battle-tested, reliable, and easy-to-implement solution, enabling Pending AI’s team to build a highly performant deployment on MongoDB Atlas. “As a startup, getting started with the community edition of MongoDB and being able to run a reliable cluster at scale was a huge benefit. Now that we’re starting to leverage the AWS infrastructure in our platform, MongoDB Atlas provides us with a fully managed solution at a low cost, and with a Private Endpoint between our AWS deployment and MongoDB cluster, we have kept latency to a minimum, and our data secure,” said Dr. David Almeida Cardoso , Vice President, Business Development at Pending AI. Output of Pending AI's Generative Molecule Designer Pending AI’s Generative Molecule Designer has been built as a machine learning model on MongoDB Atlas, trained to understand the language of pharmaceutical structures, which allows for automated production of novel compound scaffolds that can be focused and tailored to outputs of biological and/or structural studies. The Retrosynthesis Engine is also built using a set of machine learning models and MongoDB Atlas, trained to understand chemical reactions, which allows for the prediction of multiple, valid synthetic routes within a matter of minutes. “We’re also excited to explore the new Atlas Search index feature in MongoDB 7.0. We hope this will allow us to integrate some of the search functionality, which is currently complex to manage and maintain, directly into MongoDB, rather than relying on a separately maintained Elasticsearch cluster,” added Cardoso. Being part of the MongoDB AI Innovator program also allowed Pending AI to explore leveraging cloud infrastructure to scale its platform and test newer versions of MongoDB quickly and easily. Eclipse AI turns customer interaction insights into revenue Eclipse AI is a SaaS platform that turns siloed customer interactions from different sources - these can be customer calls, emails, surveys, reviews, support tickets, and more - into insights that drive retention and revenue. It was created to address the frustration of customer experience (CX) teams around the number of hours and man-weeks of effort needed to consolidate and analyse customer feedback data from different channels. Eclipse AI took on the challenge of solving this issue and worked hard to find a way to offer customers faster and more efficient ways to turn customer feedback into actionable insights. The first problem was consolidating the voice-of-customer data which was so fragmented; the second was analysing that data and turning it into specific improvement actions to improve the customer experience and prevent customer churn. Because MongoDB Atlas is a flexible document database that also can store and index vector embeddings for unstructured data, it was a perfect fit for Eclipse AI and enabled its small dev team to focus on building the product very efficiently and quickly, without being burdened with managing infrastructure. MongoDB Atlas also comes with key features such as MongoDB Atlas Device SDKs (formerly Realm) and MongoDB Atlas Search that were instrumental in bringing Eclipse AI’s platform to life. "For us, MongoDB is more than just a database, it is data-as-a-service. This is thanks to tools like Realm and Atlas Search that are seamlessly built into the platform. With minimum effort, we were able to add a relevance-based full-text search on top of our data. Without MongoDB Atlas we would not have been able to iterate quickly and ship new features fast,” commented Saad Irfani, co-founder of Eclipse AI. “Best of all, horizontal scaling is a breeze with single-click sharding that doesn't require setting up config servers or routers, reducing costs along the way. The unified monitoring and performance advisor recommendations are just the cherry on top.” Eclipse AI - MongoDB dashboard G2 rated Eclipse AI as the #1 proactive customer retention platform globally for SMEs, a recognition that wouldn’t have been possible without the use of MongoDB Atlas. Exploring your AI potential with MongoDB MongoDB Atlas is built for AI . Why? Because MongoDB specialises in helping companies and their developer teams manage richly structured data that doesn't neatly fit into the rigid rows and columns of traditional relational databases, and turn that into meaningful and actionable insights that help operationalise AI. More recently, we have added Vector Search - enabling developers to build intelligent applications powered by semantic search and generative AI over any type of data - and enhanced AWS CodeWhisperer coding assistant to our list of tools companies can use to further their AI exploration. These are just a handful of examples of what is possible in the realm of AI today. Many of our customers around the world, from start-ups to large enterprises like banks and telcos are investing in MongoDB Atlas and capabilities such as Atlas Search , Vector Search , and more to create what the future of AI and generative AI will look like in the next decade. If you want to learn more about how you can get started with your AI project, or take your AI capabilities to the next level, you can check out our MongoDB for Artificial Intelligence resources page for the latest best practices that get you started in turning your idea into an AI-driven reality.

February 5, 2024

MongoDB Doubles Down on Aotearoa as Part of Continued APAC Expansion

MongoDB is expanding its business in New Zealand to help Kiwi organisations build modern applications and take advantage of the AI opportunity that exists today. With hundreds of customers already in Aotearoa, including Pathfinder, Rapido, and Tourism Holdings, we're continuing to hire and invest to continue to grow our community in the country. Powering the next generation of modern applications Interest and excitement in AI, and particularly generative AI, has exploded. With a proud history of Innovation, it's not a surprise that many New Zealand companies are early adopters of this incredible technology. In fact, an AI Forum report has revealed that AI has the potential to increase New Zealand's GDP by as much as $54 billion by 2035. No matter what you think of the veracity of those bold predictions, one thing is sure: Almost every company is trying to figure out how to take advantage of data and software, to help them build better products, more efficiently and more quickly. Jake McInteer speaking at MongoDB.local Auckland As organisations transform into digital-first businesses, they’re faced with a growing list of application and data requirements. Modern applications are complex – they need to handle transactional workloads, app-driven analytics, full-text search, AI-enhanced experiences, stream data processing, and more. Companies are being asked to do this all while reducing data infrastructure sprawl, complexity and often also cut costs. What we are seeing globally is our developer data platform solves this challenge and complexity since it integrates all of the data services organisations need to build modern applications in a unified developer experience. Additionally, we also allow our customers to easily run anywhere in the world with over 110+ locations making us uniquely placed to enable Kiwi companies to adapt to a multicloud future. We also have strong local partnerships with all three cloud hyperscalers, all of which plan to open new cloud regions in New Zealand in the coming years. With the support of our cloud partners, in New Zealand we've already seen great adoption of MongoDB Atlas, including the largest established enterprises, through to cutting-edge startups. Here are a couple of examples. Pathfinder: Protecting vulnerable children Pathfinder , headquartered in Auckland, is a global leader in software development specialising in protecting vulnerable children. The company's mission centres on empowering law enforcement agencies with state-of-the-art technology, meticulously designed to combat the reprehensible crime of child exploitation. "We are committed to delivering investigators the most advanced tools. We cannot accept delays in removing a child from harm due to investigations being overwhelmed by large amounts of disparate data. In situations where every minute impacts a child's well-being, these tools must enable investigators to swiftly navigate data challenges, and rapidly apprehend perpetrators" said Bree Atkinson, CEO of Pathfinder Labs. Pathfinder’s Paradigm service is being built on MongoDB Atlas, running on AWS, and takes advantage of the wider developer data platform features in order to enable the next generation of data-driven investigative capabilities. By using MongoDB Atlas Vector Search , a native part of the MongoDB Atlas platform, the Pathfinder team are also able to match images and details within images (such as people and objects), classify documents and text, and build better search experiences for their users via semantic search. This enables Paradigm to efficiently aid law enforcement in identifying victims and apprehending offenders. Bree Atkinson, CEO of Pathfinder Labs, and Peter Pilly, DevOps Architect at Pathfinder Labs, with the MongoDB team in Auckland at the recent .local event "MongoDB Atlas allows our team to focus on our strengths: developing outstanding technology. It works with us not against us, enhancing integration which enables us to build better user experiences," said Peter Pilley, DevOps Architect at Pathfinder Labs. "Take MongoDB Atlas Vector Search, for example. Before MongoDB, we would have needed to incorporate multiple tools to achieve that functionality. Now we can handle it all from a single platform removing complexity and architecture that wasn't needed. With MongoDB Atlas, we're able to make data-driven decisions swiftly, boosting our productivity and decision-making speed." Peter's team at Pathfinder also uses MongoDB's performance advisor. They say it's like having an extra team member who suggests the best indexes for accessing their data, which is critical in an industry where getting to a specific piece of data could make all the difference. Rapido: Optimising B2B revenue and distribution Rapido has been utilising MongoDB Atlas for over five years. The team was originally part of MongoDB for Startups , a programme that offers startups free credits and technical advice to help them build faster and scale further. Their eagerness to adopt new technologies has enabled them to effectively harness MongoDB Atlas's evolving features. Working with the Accredo ERP system, Rapido has harnessed MongoDB Atlas to innovate in business-to-business (B2B) transactions. Using features like MongoDB Atlas Vector Search, the ' moreLikeThis ' operator, and MongoDB App Services, they've transformed business interactions, offering precise product recommendations and improved real-time visibility via change streams. Rapido's platform, which has processed orders collectively worth more than $100m to date, is essential for many wholesale businesses in New Zealand. Adam Holt, CEO of Rapido, summarises their experience: "Our journey with MongoDB Atlas has been transformative. By building on a cohesive developer data platform, we don't need to bolt-on and learn special technologies for every requirement. Continuously integrating new features keeps our platform advanced in the fast-paced B2B market. It's about leveraging technology to innovate and deliver better solutions to our clients." MongoDB expands in Aotearoa The increased demand from Kiwi organisations who are looking to innovate faster and take advantage of cutting-edge technologies, like AI, means MongoDB is now doubling down on its New Zealand footprint. Earlier this month, MongoDB established its local operations in Aotearoa, New Zealand. Jake McInteer , a native Kiwi, has officially transferred from MongoDB’s Australia business to lead the organisation in New Zealand. MongoDB already has a large, engaged community, more than 200 customers, and an extensive partner network. CEO of Lumin Max Ferguson presents at the Christchurch MongoDB user group We are incredibly excited about the opportunity to invest in and contribute to the Kiwi tech ecosystem, both to support local companies and help kiwi startups like Lumin and Marsello as well as established companies like Tourism Holdings , Figured , and Foster Moore . To support our growth, we have roles open on our Sales and Solutions Architecture team. If you are based in NZ and interested in joining our incredible team, working in our hybrid environment, please check out and apply for the roles here: Enterprise Account Executive, Acquisition Senior Solutions Architect Additionally, read here about the massive opportunity at MongoDB in APAC from our SVP Simon Eid.

November 30, 2023