MongoDB Atlas Vector Search now includes extended capabilities for querying contextual data and performance improvements to accelerate building generative AI applications

New integration with Confluent Cloud and MongoDB Atlas Vector Search allows developers to access real-time data streams from a variety of sources to fuel generative AI applications

Dataworkz, Drivly, ExTrac, Inovaare Corporation, NWO.ai, One AI, and VISO Trust among organizations building with MongoDB Atlas Vector Search

MongoDB, Inc. (NASDAQ: MDB) today at MongoDB.local London announced new capabilities, performance improvements, and a data-streaming integration for MongoDB Atlas Vector Search that make it even faster and easier for developers to build generative AI applications. Organizations of all sizes have rushed to adopt MongoDB Atlas Vector Search as part of a unified solution to process data for generative AI applications since being announced in preview in June of this year. MongoDB Atlas Vector Search has made it even easier for developers to aggregate and filter data, improving semantic information retrieval and reducing hallucinations in AI-powered applications. With new performance improvements for MongoDB Atlas Vector Search, the time it takes to build indexes is now significantly reduced by up to 85 percent to help accelerate application development. Additionally, MongoDB Atlas Vector Search is now integrated with fully managed data streams from Confluent Cloud to make it easier to use real-time data from a variety of sources to power AI applications. 

"It has been really exciting to see the overwhelmingly positive response to the preview version of MongoDB Atlas Vector Search as our customers eagerly move to incorporate generative AI technologies into their applications and transform their businesses—without the complexity and increased operational burden of 'bolting on' yet another software product to their technology stack. Customers are telling us that having the capabilities of a vector database directly integrated with their operational data store is a game changer for their developers," said Sahir Azam, Chief Product Officer at MongoDB. "This customer response has inspired us to iterate quickly with new features and improvements to MongoDB Atlas Vector Search, helping to make building application experiences powered by generative AI even more frictionless and cost effective."

Many organizations today are on a mission to invent new classes of applications that take advantage of generative AI to meet end-user expectations. However, the large language models (LLMs) that power these applications require up-to-date, proprietary data in the form of vectors—numerical representations of text, images, audio, video, and other types of data. Working with vector data is new for many organizations, and single-purpose vector databases have emerged as a short-term solution for storing and processing data for LLMs. However, adding a single-purpose database to their technology stack requires developers to spend valuable time and effort learning the intricacies of developing with and maintaining each point solution. For example, developers must synchronize data across data stores to ensure applications can respond in real time to end-user requests, which is difficult to implement and can significantly increase complexity, cost, and potential security risks. Many single-purpose databases also lack the flexibility to run as a managed service on any major cloud provider for high performance and resilience, severely limiting long-term infrastructure options. Because of these challenges, organizations from early-stage startups to established enterprises want the ability to store vectors alongside all of their data in a flexible, unified, multi-cloud developer data platform to quickly deploy applications and improve operational efficiency.

MongoDB Atlas Vector Search addresses these challenges by providing the capabilities needed to build generative AI applications on any major cloud provider for high availability and resilience with significantly less time and effort. MongoDB Atlas Vector Search provides the functionality of a vector database integrated as part of a unified developer data platform, allowing teams to store and process vector embeddings alongside virtually any type of data to more quickly and easily build generative AI applications. Dataworkz, Drivly, ExTrac, Inovaare Corporation, NWO.ai, One AI, VISO Trust, and many other organizations are already using MongoDB Atlas Vector Search in preview to build AI-powered applications for reducing public safety risk, improving healthcare compliance, surfacing intelligence from vast amounts of content in multiple languages, streamlining customer service, and improving corporate risk assessment. The updated capabilities for MongoDB Atlas Vector Search further accelerate generative AI application development:

• Increase the accuracy of information retrieval for generative AI applications: Whether personalized movie recommendations, quick responses from chatbots for customer service, or tailored options for food delivery, application end-users today expect accurate, up-to-date, and highly engaging experiences that save them time and effort. Generative AI is helping developers deliver these capabilities, but the LLMs powering applications can hallucinate (i.e., generate inaccurate information that is not useful) because they lack the necessary context to provide relevant information. By extending MongoDB Atlas's unified query interface, developers can now create a dedicated data aggregation stage with MongoDB Atlas Vector Search to filter results from proprietary data and significantly improve the accuracy of information retrieval to help reduce LLM hallucinations in applications.
  
  
• Accelerate data indexing for generative AI applications: Generating vectors is the first step in preparing data for use with LLMs. Once vectors are created, an index must be built for the data to be efficiently queried for information retrieval—and when data changes or new data is available, the index must then be updated. The unified and flexible document data model powering MongoDB Atlas Vector Search allows operational data, metadata, and vector data to be seamlessly indexed in a fully managed environment to reduce complexity. With new performance improvements, the time it takes to build an index with MongoDB Atlas Vector Search is now reduced by up to 85 percent to help accelerate developing AI-powered applications.
  
  
• Use real-time data streams from a variety of sources for AI-powered applications: Businesses use Confluent Cloud's fully managed, cloud-native data streaming platform to power highly engaging, responsive, real-time applications. As part of the Connect with Confluent partner program, developers can now use Confluent Cloud data streams within MongoDB Atlas Vector Search as an additional option to provide generative AI applications ground-truth data (i.e. accurate information that reflects current conditions) in real time from a variety of sources across their entire business. Configured with a fully managed connector for MongoDB Atlas, developers can make applications more responsive to changing conditions and provide end user results with greater accuracy.

Organizations Already Innovating with MongoDB Atlas Vector Search in Preview

Dataworkz enables enterprises to harness the power of LLMs on their own proprietary data by combining data, transformations, and AI into a single experience to produce high-quality, LLM-ready data. "Our goal is to accelerate the creation of AI applications with a product offering that unifies data, processing, and machine learning for business analysts and data engineers," said Sachin Smotra, CEO and co-founder of Dataworkz. "Leveraging the power of MongoDB Atlas Vector Search has allowed us to enable semantic search and contextual information retrieval, vastly improving our customers' experiences and providing more accurate results. We look forward to continuing using Atlas Vector Search to make retrieval-augmented generation with proprietary data easier for highly relevant results and driving business impact for our customers."

Drivly provides commerce infrastructure for the automotive industry to programmatically buy and sell vehicles through simple APIs. "We are using AI embeddings and Atlas Vector Search to go beyond full-text search with semantic meaning, giving context and memory to generative AI car-buying assistants," said Nathan Clevenger, Founder and CTO at Drivly. "We are very excited that MongoDB has added vector search capabilities to Atlas, which greatly simplifies our engineering efforts."

ExTrac draws on thousands of data sources identified by domain experts, using AI-powered analytics to locate, track, and forecast both digital and physical risks to public safety in real-time. "Our domain experts find and curate relevant streams of data, and then we use AI to anonymize and make sense of it at scale. We take a base model and fine-tune it with our own labeled data to create domain-specific models capable of identifying and classifying threats in real-time," said Matt King, CEO of ExTrac. "Atlas Vector Search is proving to be incredibly powerful across a range of tasks where we use the results of the search to augment our LLMs and reduce hallucinations. We can store vector embeddings right alongside the source data in a single system, enabling our developers to build new features way faster than if they had to bolt-on a standalone vector database—many of which limit the amount of data that can be returned if it has meta-data attached to it. Because the flexibility of MongoDB's document data model allows us to land, index, and analyze data of any shape and structure—no matter how complex—we are now moving beyond text to vectorize images and videos from our archives dating back over a decade. Being able to query and analyze data in any modality will help us to better model trends, track evolving narratives, and predict risk for our customers."

Inovaare Corporation is a leading provider of AI-powered compliance automation solutions for healthcare payers. "At Inovaare Corporation, we believe that healthcare compliance is not just about meeting regulations but transforming how healthcare payers excel in the entire compliance lifecycle. We needed a partner with the technological prowess and one who shares our vision to pioneer the future of healthcare compliance," said Mohar Mishra, CTO and Co-Founder at Inovaare Corporation. "MongoDB's robust data platform, known for its scalability and agility, perfectly aligns with Inovaare's commitment to providing healthcare payers with a unified, secure, and AI-powered compliance operations platform. MongoDB's innovative Atlas Vector Search powers the reporting capabilities of our products. It allows us to deliver context-aware compliance guidance and real-time data-driven insights."

NWO.ai is a premier AI-driven Consumer Intelligence platform helping Fortune 500 brands bring new products to market. "In today's rapidly evolving digital age, the power of accurate and timely information is paramount," said Pulkit Jaiswal, Cofounder of NWO.ai. "At NWO.ai, our flagship offering, Worldwide Optimal Policy Response (WOPR), is at the forefront of intelligent diplomacy. WOPR harnesses the capabilities of AI to navigate the vast oceans of global narratives, offering real-time insights and tailored communication strategies. This not only empowers decision-makers but also provides a vital counterbalance against AI-engineered disinformation. We're thrilled to integrate Atlas Vector Search into WOPR, enhancing our ability to instantly search and analyze embeddings for our dual-use case. It's an exciting synergy, and we believe it's a testament to the future of diplomacy in the digital age."

One AI is a platform that offers AI Agents, Language Analytics, and APIs, enabling seamless integration of accurate, production-ready language capabilities into products and services. "Our hero product - OneAgent - facilitates trusted conversations through AI agents that operate strictly upon company-sourced content, secured with built-in fact-checking," said Amit Ben, CEO and Founder of One AI. "With MongoDB Atlas, we're able to take source customer documents, generate vector embeddings from them that we then index and store in MongoDB Atlas Vector Search. Then, when a customer has a question about their business and asks one of our AI agents, Atlas Vector Search will provide the chatbot with the most relevant data and supply customers with the most accurate answers. By enabling semantic search and information retrieval, we're providing our customers with an improved and more efficient experience."

VISO Trust puts reliable, comprehensive, actionable vendor security information directly in the hands of decision-makers who need to make informed risk assessments. "At VISO Trust, we leverage innovative technologies to continue our growth and expansion in AI and security. Atlas Vector Search, combined with the efficiency of AWS and Terraform integrations, has transformed our platform," said Russell Sherman, Cofounder and CTO at VISO Trust. "With Atlas Vector Search, we now possess a battle-tested vector and metadata database, refined over a decade, effectively addressing our dense retrieval requirements. There's no need to deploy a new database, as our vectors and artifact metadata can be seamlessly stored alongside each other."

Session Will Discuss Consumer Trends and Next-Gen Solutions to Help Retailers Appeal to the Modern Shopper and Ensure Success in a Volatile eCommerce Market

GroupBy, a SaaS-based eCommerce product discovery and search leader, announces its upcoming panel discussion, “6 Key eCommerce Strategies To Help You Bridge The Gap Between Consumer and Merchant.” The session, hosted by GroupBy, will take place on Thursday, October 12, at 1 p.m. ET/10 a.m. PT.

During this panel session, guest speaker Brendan Witcher, VP and Principal Analyst with Forrester, will join GroupBy’s Director of Product, Arv Natarajan. They will discuss the AI-forward strategies and initiatives eCommerce retailers should be prioritizing to set themselves apart from their competition and ensure future success.

Topics covered during the session will include:

• Striking a balance between AI and manual intervention
• How to use AI technology to operationalize your business to create better customer experiences
• Why eCommerce retailers must blend their omnichannel experiences with personalization to deliver true value to their customers
• Why modern retailers are switching from rule-based to revenue-generating merchandising
• Ways to secure a predictable revenue stream to future proof your business

“Though retail sales are projected to increase this year, inflation and economic uncertainty are putting pressure on retailers, exacerbating challenges with attracting and retaining customers,” says Natarajan. “That’s why it’s critical to provide great customer experiences, and in 2023, retailers have more tools than ever at their disposal to create them. I’m excited to join Brendan to address some of these challenges retailers face going into the busy shopping season and share some of these cutting-edge, future-focused solutions that can help them face those challenges head-on.”

GroupBy’s mission is to create the world's most relevant and highly converting websites, all while requiring less effort and cost to build and run. By leveraging Google’s Cloud Discovery AI, which was specifically designed for eCommerce use cases, GroupBy’s AI-first eCommerce Search and Product Discovery Platform delivers relevant, buyable, personalized search results that are optimized for revenue.

By enabling AI-led optimization, while still ensuring merchandisers have the business controls they require, GroupBy’s platform simultaneously frees up merchandising teams to work on higher-value business initiatives, while optimizing search for revenue and boosting key sitewide metrics like AOV, conversion rate and revenue per search.

Reply launches a proprietary framework for generative AI-based software development, KICODE Reply. By integrating generative AI models, the Reply framework introduces a completely new approach, capable of supporting all phases of the software development lifecycle: from creating user stories, to collecting requirements, and designing, coding, testing, and deployment. The new framework has been developed by Ki Reply, a company within the Reply Group specializing in AI-supported software development, enhances software efficiency and overall quality by automating repetitive tasks.

KICODE Reply, with a Task-Driven Autonomous Agent System architecture, understands natural language commands and breaks them down into secondary operations that are distributed to various agents, much like n intelligent automation systems. These agents act as product owners, front-end or back-end developers, or DevOps engineers, autonomously performing tasks based on user or external agent-provided goals and information. Users can control the KICODE Reply framework through an interface, and assign new development tasks, or alternatively, they can interact with the framework through integration into common software development platforms like GitHub or GitLab via webhooks.

KICODE Reply offers users flexibility, modularity, and scalability, enabling software development in a matter of minutes. With KICODE Reply, developers can be assisted with simple and repetitive tasks, allowing them to focus on more complex activities and unleash their creativity. For example, KICODE Reply does not require a precise description of requirements, but generates a user story based on a simple project goal description and autonomously achieves it step by step.

Several companies are already experimenting with the KICODE Reply framework to enhance their software development process, including a leading automotive company collaborating with Ki Reply. They are currently working on a Proof of Concept (PoC) to determine the suitability of different agents for managing integration requests and test generation.

Advertising is transformed for non-DTC & DTC products with headless checkout, allowing platforms and marketplaces to leverage first-party data, optimizing campaign performance

Shoppable®, today, released its Shoppable® Checkout API™ to the general public in a full production launch. This turn-key solution is meant to reduce the difficulty, expense, labor, and time commitment for companies transitioning from third-party to first-party data.

Shoppable's ecommerce APIs utilize the proven 3x patented technology of Universal Checkout, a multi-retailer, multi-product, seamless interface shown to increase conversion, decrease cart abandonment, and grow new sales. Over 400 million SKUs are available through Shoppable's API including products from Walmart, Target, and Best Buy. Through the consented collection of consumer demographics and shopping behavior via commerce, more effective targeting and personalization can be obtained, while protecting privacy.

Founder & CEO of personal fashion innovator Aesthetic, LJ Northington, was an early adopter, "Shoppable's Universal Checkout is in alignment with Aesthetic's goals to increase conversion for brands, improve the customer journey, and revolutionize the way that consumers purchase products online."

Heather Udo, the founder and CEO of Shoppable®, states, "With Shoppable® Checkout API™, marketers and advertising technology platforms replace cookies with the more accurate 1st party data gathered from their own customers. Marketers can track closed-loop campaign data, easily recognize the most profitable segments, and even build lookalike audiences for future marketing campaigns. It's a competitive advantage."

CEO of ResponsiveAds, the ad tech leader known for its beautiful display formats, Matthew Snyder, adds, "We have been extremely successful with click-to-site shoppable dynamic ads. Using the new Shoppable® Checkout API™, our clients can extend their offerings to enable consumers to buy-in-ad and close-the-loop within a single ad session. Along with our universal Fully-Fluid™ format across display, apps, CTV, and DOOH, the Shoppable® Checkout API™ will enable a full attribution process. The API will extend our unique analytics to, holistically, include all stages from an impression, click, add-to-cart, and checkout event. This, in addition to creating an optimized retail media experience for consumers."

The multi-retailer/multi-product innovation of Shoppable's API has been shown to have a 25% conversion rate improvement (compared to traditional ecommerce) and up to a 700% improvement over affiliate link-off solutions, resulting in a significant increase in sales.

63.2% of surveyed companies noted a year-on-year boost in their mobile app performance marketing budgets

Moloco and Ipsos partnered together to gauge perspectives from mobile app marketers in nine countries

37% of respondents selected Advanced ML/AI as the key business factor when vetting mobile app performance marketing vendors above all other considerations.

Moloco, a leader in operational machine learning (ML) and performance advertising, together with leading independent research company Ipsos, today announced the findings of the inaugural Mobile App Performance Marketing Global Report. More than 1,600 mobile app marketers were surveyed across nine countries, including US, UK, Korea, France, Germany, Indonesia, Japan, Singapore, and Vietnam.

“The global shift in marketing from reach to results continues to gain momentum across different countries and various industries,” said Daisuke Yokokawa, Vice President, Global Marketing, Moloco. “Many mobile app marketers are aware that the secret of big tech's success in advertising is advanced ML technology and the performance marketing solutions that they provide. This global trend is due to the clear and resounding power that mobile app performance marketing has to drive revenue, user acquisition, and profit, especially during times of economic uncertainty.”

The study revealed that:

• Performance mobile app marketing continues to grow consistently across all industries. In 2023, 64.7% of surveyed companies increased their mobile ads marketing budget compared to the previous year. On average, surveyed companies increased their mobile ads marketing budget by approximately 25.7%. In addition, 63.2% of surveyed companies reported that they would be increasing the performance marketing portion of their overall mobile ads budget from 2022. Performance marketing claimed 45.7% of the mobile ads budget in 2023, surpassing brand marketing at 41.4%. Performance marketing is consistently recognized as an important investment for boosting sales and profits.
• The virtuous cycle of performance-driven marketing drives user acquisition and improves Return on Ad Spend (ROAS). Companies adept in performance-driven mobile marketing programs have demonstrated high satisfaction, scoring 4.4 out of 5, crediting performance marketing with successfully acquiring new users, acquiring high-quality users, and improving ROAS. 58.2% of marketers saw performance marketing as more effective for driving revenue growth than traditional brand marketing. And 55.5% of marketers view performance marketing as the key to profitability during times of economic uncertainty.
• Advanced machine learning scores highest as the #1 factor when selecting a mobile app performance marketing solution. ML is the key success factor for global marketers, with 37% of them selecting “advanced ML/AI technology” as the most important from a list of 10 possible factors. Other important factors are global reach (23.1%) and high-quality user acquisition (18.1%), which ranked second and third respectively. The role of machine learning is credited with providing real-time, accurate data for decision-making and goal monitoring.

“Performance marketing is on trend, regardless of the country,” said Jennifer Ha, Partner of Ipsos Strategy3, Project Leader. “Marketers are typically loath to share their best kept secrets, but thanks to this anonymized research study, we now have detailed insights about their strategic marketing decisions and investments. Ultimately, having consistent results such as measurable and impactful ROAS underpins the success of many global performance marketing budgets.”

Methodology

Moloco partnered with Ipsos to conduct an online survey targeting mobile app marketers in nine countries between April 3-May 1, 2023. The survey consisted of multiple-choice questions designed to gather detailed insights. Care was taken in question design to minimize bias and ambiguity, and all responses were anonymized to encourage honesty.

The survey was defined as:

• A sample of 1,675 marketers working at companies owning mobile apps and app marketers at marketing agencies from the US (300), the UK (225), Germany (190), France (207), Korea (146), Japan (100), Singapore (184), Vietnam (169), and Indonesia (154) across various industries
• Among the respondent criteria are marketers directly involved and responsible for mobile app marketing budget execution

Cabiri, a boutique systems integrator renowned for its expertise in composable commerce, proudly introduces Launch. This groundbreaking solution is purpose-built to address the unique challenges faced by rapidly growing enterprises in the modern digital commerce landscape.

Key Features of Launch:

Speed and Efficiency: Deploy a robust composable commerce platform in just 8 weeks. Launch offers enterprises a fast, efficient and notably lower-risk pathway to modern digital transformation.

Future-Proof Design: Launch doesn't just cater to the present. It's built to scale, ensuring technology evolves hand-in-hand with business growth.

Power of Leading SaaS Products: By harnessing the capabilities of enterprise-grade SaaS products such as Commerce Layer, Sanity, Vercel, and Algolia, Launch ensures businesses receive an all-in-one, interconnected package.

Seamless Integration: Designed to effortlessly meld with existing systems, Launch minimises technological disruption, ensuring unparalleled speed to market.

Global Operations Support: Whether you're serving a local audience or operating on a global scale, Launch stands ready to back every enterprise's expansive ambitions.

“We recognised a gap in the market for a solution that not only addresses today's commerce needs but also scales for tomorrow. Launch embodies that vision, delivering an agile, powerful, and scalable solution.” - Dan Kain, the CTO at Cabiri.

“Cabiri's new Launch Accelerator is a powerful innovation that integrates best-in-class components to form an enterprise-grade digital experience platform. We are eager to work closely with Cabiri to help brands transition to composable commerce and take their business to the next level. Cabiri's Launch accelerator is now available for any enterprise interested in going-to-market with a capital efficient solution in as quick as 8 weeks. Cabiri and its partners hope to scale this solution to support the addressable market of high growth enterprises in Europe, North America, and beyond.” - Fillipo, Commerce Layer.

Today, global affiliate marketing platform Awin announces the launch of its upgraded features, creating a new digital marketing ecosystem that addresses the challenges faced by brands and online publishers worldwide. In an ad landscape dominated by a handful of large tech firms, and with brands demanding more transparency, these upgrades introduce game-changing solutions that empower brands to regain control over their ad spend, create lasting marketing partnerships and generate more revenue.

The Challenge: Big Tech’s Dominance of Digital Ad Spend

Almost three-quarters of global digital ad spend is currently invested into three main technology platforms, whose market dominance and auction-based models have left businesses struggling with skyrocketing costs and little control over where to invest their money.

Similarly, the US Association of National Advertisers’ (ANA) recent study revealed that 23% of brand spend in programmatic is going to waste, highlighting the transparency issues within that space. This wasted spend amounts to at least $20bn, a third more than is set to be invested globally in the affiliate industry by brands this year.

The Solution: Choice, Control, Customisation, and ROI

Awin recognises the need for an alternative as companies increasingly prioritise their own bottom line and look for media investments they can trust. Its upgraded platform is a direct response to the demand from ecommerce brands for an advertising solution that is both adaptable and transparent, empowering them to achieve their marketing goals in an increasingly competitive environment.

The Awin partner ecosystem allows brands to confidently break free from these costly models, offering:

• Choice: Brands can quickly discover and choose from over 1 million affiliate partners that align with their marketing objectives via Awin’s AI-powered Partner Discovery tool.
• Control: Brands can easily measure the value and impact of their investments using new in-depth funnel and journey path reports to understand how their customers find them online. And powerful sector benchmarking shows how they stack up against competitors.
• Customisation: Brands can use new datapoints and flexible compensation models to create custom incentives that focus only on the most valuable marketing actions, ensuring cost efficiency.
• ROI: With their affiliate programmes built to drive highly-targeted marketing value, brands can enjoy a 14:1 return on their ad investment when working with Awin.

"Choice, control, and customisation are critical to creating mutually beneficial and lasting relationships in any business, particularly within digital marketing," said Adam Ross, CEO of Awin. "Awin’s partner ecosystem helps ecommerce brands eliminate industry silos, complex integrations and wasteful spending to create their own advertising ecosystems that easily scale based on individual needs. We’re excited to help customers take back control of their marketing, giving them the freedom to grow their own way.