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MongoDB Atlas Vector Search simplifies generative AI and semantic search capabilities into …

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Posted on mongodb google news. Visit mongodb google news

MongoDB is a source-available, cross-platform, document-oriented database program. Classified as a NoSQL database product, MongoDB utilizes JSON-like documents with optional schemas. MongoDB is developed by MongoDB Inc., and current versions are licensed under the Server Side Public License.

Himanshumali, Principal Solutions Architect in India, MongoDB, tells us more. Excerpts from an interview:

DQ: What is your India business strategy? Explain the success and challenges that you have faced in the India market?

Himanshumali: With a robust foundation established in India, our organization boasts a workforce comprising 500+ dedicated individuals and 3,100 customers in India. That number is growing at more than 40% year on year. Our primary objective within the Indian market is to provide developers, technological innovators, and enterprises with the tools and support they need to effortlessly create cutting-edge, scalable software and applications.

As we continue to expand our presence, our teams are delving further into the realm of enterprise solutions, catering to the needs of some of the nation’s most prominent businesses.

MongoDB Atlas is one of the most critical, must-have technology platforms because it is uniquely positioned to enable organizations of all shapes and sizes to modernize, innovate, and deliver the business outcomes that drive success—all on one developer data platform.

MongoDB gives its tens of thousands of customers the best platform for building AI applications with Atlas—across the enterprise for any workload, with new capabilities that are critical for organizations today and necessary to usher in the next technological shift in software we’re seeing. Some of our key clients who’ve benefited from Atlas are TATA Digital, Adani Digital, Canara HSBC Life Insurance, Zomato, TATA AIG general Insurance and many others.

MongoDB is dedicated to empowering developers in India by providing essential tools and support for creating cutting-edge, scalable software and applications. We firmly believe that developers play a crucial role in the growth of Indian companies. MongoDB is also actively involved in organizing local events, workshops, webinars, hackathons, and other initiatives. This multifaceted approach underscores MongoDB’s commitment to nurturing a thriving developer community in India.

The success and impact MongoDB has achieved in India showcase its dedication to driving technological advancements and facilitating business growth through innovative and scalable solutions.

DQ: AI is becoming a central part of every technology company today. What is MongoDB’s AI play?

Himanshumali: According to Gartner, the prevalence of generative artificial intelligence (GenAI) application programming interfaces (APIs) or models is expected to surpass 80% adoption among enterprises by 2026. This underscores the growing significance of AI in shaping the future of business operations. Recognizing this trend, MongoDB is committed to empowering developers and enhancing their experience throughout the entire application development cycle by integrating AI into its products and services.

GenAI, with its ability to initiate new code creation and automate operational processes, stands out as a powerful tool in augmenting developer productivity. By reducing repetitive tasks, AI-driven tools enable developers to channel their efforts into impactful innovation.

MongoDB is actively leveraging this potential to benefit developers who are rapidly deploying modern, data-driven applications on MongoDB with minimal friction. Vector search and, more broadly, AI, are more popular now than ever. These terms are arising everywhere. Technology companies around the globe are scrambling to release vector search and AI features in an effort to be part of this growing trend.

As a result, it’s unusual to come across a homepage for a data-driven business and not see a reference to vector search or large language models (LLMs). In this blog, we’ll cover what these terms mean while examining the events that led to their current trend.

Atlas Vector Search helps to search unstructured data. One can create vector embeddings with machine learning models like OpenAI and Hugging Face, and store and index them in Atlas for retrieval augmented generation (RAG), semantic search, recommendation engines, dynamic personalization, and other use cases. With Atlas Vector Search, developers can build AI-powered experiences while accessing all the data they need through a unified and consistent developer experience in the form of the MongoDB Query API.

Additionally, MongoDB very recently announced plans to integrate MongoDB Atlas Vector Search with Amazon Bedrock to enable organizations to build next-generation applications on Amazon Web Services (AWS) and their industry-leading cloud infrastructure.

MongoDB Atlas Vector Search uses an organization’s operational data to simplify bringing generative AI and semantic search capabilities into applications for highly engaging and customized end-user experiences. This integration will make it easier for developers to create applications on AWS that use generative AI to complete complex tasks for a wide range of use cases and deliver up-to-date responses based on proprietary data processed by MongoDB Atlas Vector Search.

Overall, we recognize the transformative power of AI in developer workflows, and are dedicated to providing tools and services that not only keep pace with industry trends but also empower developers to drive innovation in the ever-evolving landscape of technology in India.

DQ: How does MongoDB’s offerings help developers in creating more efficient and innovative AI based applications?

Himanshumali: MongoDB’s strategic integration of AI into its products and services is a game-changer for developers, facilitating the creation of more efficient and innovative AI-based applications. With features like natural language processing in MongoDB Compass, developers can rapidly generate executable MongoDB Query API syntax, streamlining the development process and simplifying application building on the MongoDB platform.

Additionally, AI-driven data visualizations in Atlas Charts empower customers to extract data-driven insights faster, enabling high-velocity decision-making. The automated conversion of SQL queries to MongoDB Query API syntax within MongoDB Relational Migrator eliminates tedious tasks, allowing developers to migrate large monolithic applications seamlessly and efficiently, without downtime.

Moreover, the interactive chatbot in MongoDB Documentation enables developers to ask technical questions and troubleshoot challenges, receiving detailed and intelligent support instantly. These innovations not only enhance productivity but also provide developers with a head start in building high-performing applications with sophisticated capabilities.

MongoDB’s offerings cater to a broad spectrum of customers across industries, from startups to large enterprises, highlighting its pivotal role in the development and scaling of applications.

MongoDB, and Amazon Web Services, recently announced their collaboration for Amazon CodeWhisperer and to further provide enhanced suggestions for application development and modernization on MongoDB’s industry-leading developer data platform that millions of developers and tens of thousands of customers rely on every day for business-critical applications.

MongoDB Inc. also announced the general availability of MongoDB Atlas Vector Search and MongoDB Atlas Search Nodes to make it faster and easier for organizations to securely build, deploy, and scale next-generation applications at less cost.

MongoDB Atlas Vector Search simplifies bringing generative AI and semantic search capabilities into real-time applications for highly engaging and customized end-user experiences using an organization’s operational data. MongoDB Atlas Search Nodes provide dedicated infrastructure for applications that use generative AI and relevance-based search to scale workloads independent of the database and manage high-throughput use cases with greater flexibility, performance, and efficiency.

Together, these capabilities on MongoDB Atlas provide organizations with the required foundation to seamlessly build, deploy, and scale applications that take advantage of generative AI and robust search capabilities with greater operational efficiency and ease of use.

DQ: Please share some names of start-up and enterprise customers along 1-2 short case studies.

Himanshumali: Some of the notable examples of our Indian customers include where MongoDB played a crucial role in their success includes:

  • Darwinbox, since its inception in 2015, Darwinbox has experienced remarkable growth, evolving into a global HR Software-as-a-Service (SaaS) platform with a presence in 116 countries, serving over 850 customers and accommodating more than 2.2 million daily users. The platform, supported by MongoDB Atlas, efficiently manages the vast volume of data generated, exceeding 250TB. MongoDB’s document-based database, scalable architecture, and robust security seamlessly address Darwinbox’s needs.

The aggregation framework of MongoDB ensures impressive performance, delivering near real-time insights for HR leaders. With MongoDB Atlas, the complexities of internal management, including configurations, upgrades, monitoring, and backups, are streamlined, offering a lean architecture and efficient managed services. The flexibility of MongoDB proves invaluable for Darwinbox, enabling easy adaptation to new changes or customizations in their dynamic and expansive operations.

  • Zomato is one of India’s largest consumer technology companies. The restaurant aggregator and food delivery operator provide restaurant information, menus and user reviews, and food delivery options from partner restaurants in over 1,000 Indian cities and towns. With over 17.5 million customers, 220,000 restaurant partners and 350,000 delivery partners, Zomato deals with data in huge quantities.

However, in 2017 Zomato became increasingly aware of the pain points of database management. Using features such as index suggestions, geospatial queries and analytics nodes, MongoDB is now the driving force behind many of Zomato’s key operational systems such from order tracking, assignment, order details to the delivery partner expected earnings, featured restaurants and delivery partner onboarding system and more.

DQ: Please elaborate on MongoDB’s AI Innovators Program?

Himanshumali: The MongoDB AI Innovators Program is a program designed to help early-stage startups build AI-powered solutions and bring them to market more quickly. The program offers free credits for MongoDB products, including Atlas Database, Atlas Vector Search, Atlas Search, Atlas App Services, and more, to supercharge data infrastructure. Startups can receive dedicated one-on-one sessions with experts to receive personalized recommendations to add scale and solve problems.

The program also offers opportunities to collaborate with MongoDB’s product and partner teams, and to create go-to-market partnerships with MongoDB. The program consists of the AI Startups track for early-stage ventures and the AI Amplify track for more established organizations. The program is intended for startups at Series A or earlier, building a product or service. Startups must have already been accepted into the MongoDB for Startups program to be eligible for the AI Innovators track.

DQ: How are you seeing the AI trend play out in India?

Himanshumali: While more and more companies in India are integrating AI in India, there is definitely a skill gap that needs to be bridged. Many Indian organizations are struggling to find developers with the skills needed to build modern applications and take advantage of new technologies like generative AI that are propelling a wave of innovation and disrupting industries.

According to a report by the NASSCOM, only 35% of the 800,000-computer science, IT, and math graduates in India possessed the necessary skills required to enter high-demand tech roles. This gap underscores the need for increased collaboration between industry and academia to provide the real-world training needed to upskill students and educators in India to meet the demands of the country’s large and growing tech industry.

Our Academia program in India gives educators and students the knowledge and skills needed to help close this gap by learning how to use MongoDB Atlas, which integrates all the data services needed to build modern applications with a unified developer experience.

Under the program, students and educators get access to hundreds of thousands of dollars’ worth of MongoDB Atlas credits as well as free certification that validates developer skills on MongoDB to employers. Free curriculum resources and training to help students gain the skills they need to build, manage, and deploy modern, business critical applications.

Article originally posted on mongodb google news. Visit mongodb google news

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