Powering Vector Search Maturity in Retail with Pureinsights

Genevieve Broadhead and Phil Lewis, Pureinsights
December 14, 2023 | Updated: August 8, 2024
#Retail#genAI#Vector Search

In a competitive retail market, with customer demands higher than ever, retailers are on a constant journey toward search maturity. With the recent announcement of MongoDB’s Vector Search offering, retailers are implementing smarter search solutions to provide customers and staff with delightful experiences. Here we’ll explore how partners like Pureinsights are helping retailers to understand what true search maturity entails, and how to start their vector search journey on MongoDB Atlas.

Check out our AI resource page to learn more about building AI-powered apps with MongoDB.

How MongoDB Partners Like Pureinsights Can Help

Search and AI application specialists like Pureinsights can shorten the planning and development cycle, bring applications to production faster, and accelerate time to value for the customer.

The Architecture of Vector Search Applications

Virtually every Vector Search application will follow the basic logical flow illustrated below.

A Client creates a complex query, which is then submitted to an encoder. The encoder turns the query into a Vector and submits it to the Vector Search Engine. The Vector Search engine searches the Vector Database and returns results, which are then formulated and returned to the Client for presentation.

Diagram depicting the Vector Search data workflow. Data starts with the client, and then through read and writes flows into Encoder. From there, it flows into the Vector Search Engine through vectors.

A complete Vector Search application includes all of the elements in this diagram, but not all of them are currently provided in the MongoDB Atlas platform. Everything to the left of the Vector Search Engine has to be developed by someone. MongoDB provides the vector store and a means to search it, but someone has to build the client and logic for the complete application.

Why Involve Pureinsights to build your Vector Search applications?

Pureinsights is a MongoDB BSI partner and has extensive knowledge and expertise in helping customers accelerate time-to-production of premier search applications.

Pureinsights specializes in search applications and provides services to build end-to-end vector search solutions, including solutions to create and populate MongoDB Vector Search and UI/Client to search MongoDB Atlas using Atlas Search and Atlas Vector Search. Customers can focus on their core business while we do the development.

Pureinsights Search Maturity Matrix – A Roadmap for Better Search, including Vector Search

All of the use cases we discussed – e-commerce search, AI-powered search for support, and product information/reviews are advanced search features for Retail. But it’s always best to walk before you run, so before implementing Vector Search, a good strategy is to make sure your current applications have been optimized. Pureinsights methodology for search applications includes analyzing the state of current applications using a Search Maturity Matrix.

Pureinsights - Design, Build, and Manage

After mapping out their journey to build out advanced search capabilities for their retail applications, Pureinsights can help customers build the applications on the MongoDB Atlas Platform from design, to build, to operations.

Application Design and Architecture: A well-defined plan is the key to efficient application development. Pureinsights with their immense experience can help with complex design decisions, such as choosing the right AI models and creating the best architecture for performance and security.

Application Build: With over 20 years of experience in search, Pureinsights can help you build and deploy your Atlas Search application quickly and efficiently. Pureinsights has developed methodologies and frameworks like the Pureinsights Discovery Platform, which work with AI technologies (e.g., ChatGPT) and integrate with the Atlas platform to reduce development time and accelerate time to production.

Managed services: Pureinsights can even run your search application for you with our SearchOps and maintain it for optimum performance with their fully managed service so you can focus on your core business.

Conclusion

Pureinsights can help customers overcome the challenges of building vector search applications and accelerate the time to production. With their expertise in application design, build, and managed services, Pureinsights can help customers build and deploy next-generation vector search applications that deliver real business value.

Is your e-commerce store ready for AI? And are your products as easy to find as your competitors? Modern consumer expect flawless search experiences in mobile and online e-commerce search. Join MongoDB and Pureinsights on Tuesday, January 23, at 1pm ET for an insightful new webinar hosted by Digital Commerce 360 to learn:

  • What is the search Maturity Matrix, and which capabilities are your organization missing to achieve better results

  • How retailers are building smarter search applications with AI

  • What's possible with MongoDB's new Vector Search offering

Related resources:

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WOO Network借重MongoDB Atlas優勢 持續優化WOO X平台服務能量

首創跨領域加密貨幣交易平台 全力提升交易深度與流通性 2009年問世的比特幣，以區塊鏈、去中心化等技術，快速改變傳統金融產業的發展模式，也帶動全球加密貨幣的蓬勃發展，成為時下最熱門的數位商品之一。許多商家已經接受比特幣、乙太幣等加密貨幣進行交易，吸引更多人開始投資加密貨幣，導致全球的加密貨幣交易所數量快速增加，彼此之間競爭更為激烈。 2019 年，WOO Network由加密貨幣交易公司Kronos Research 開發，將交易者、交易所、機構和 DeFi 平台串連。其後WOO Network 創立WOO X 加密貨幣交易所，以大眾化的方式、低交易成本，為用戶提供高流動性和精準的交易體驗。 WOO Network Backend Engineer林宣丞說，面對日益蓬勃的加密貨幣市場，我們透過成立 WOO X 交易平台，提供有別於傳統交易所的服務模式，藉由易於操作的交易平台介面、低廉手續費，讓一般用戶能以最輕鬆方式跨入加密貨幣領域。因應產業競爭日趨激烈，我們必須提供更多元化的服務，以及符合用戶期待的產品，才能維持在市場上的主導地位，而MongoDB Atlas正是我們不可或缺的首選方案。 挑戰 業務成長快速影響服務效能 引進NoSQL迫在眉睫 WOO X平台為用戶提供極低的交易成本、自行定義使用者介面，且支援多種交易組合等，問世之後隨即在市場獲得好評，也讓整體業績快速成長。在亮眼成績的背後，WOO Network發現WOO X平台原本採用的關聯式資料庫，已難以支撐業務快速發展，導致系統回應時間、傳輸介面等出現效能下滑的狀況。其次，在市場資訊、用戶等資料量同步成長的狀況下，也讓資料查詢速度變得非常慢。狀況若不改善，勢必會嚴重影響到使用者體驗，促使該公司開始尋找合適的NoSQL資料庫方案。 林宣丞表示，「加密貨幣市場變化非常快，交易所必須提供最即時、精準的資訊，否則有可能讓用戶產生交易上的損失。由於WOO X平台交易費低、使用介面友善，所以在很短時間內吸引了眾多用戶加入，也讓整體交易量超出原先設定的負擔範圍。因此，我們必須主動進行修正、優化，以提升維護和效能，保持市場的領先地位。MongoDB Atlas能在Google Cloud Platform (GCP) 上運作，自然是解決前述問題的首選方案。」 解決方案 快速擴充、高彈性、易於維運 MongoDB Atlas獨步全球市場 市面上No SQL產品不少，甚至三大公有雲平台也有相關方案，WOO Network綜合考慮不同因素後最終選擇了MongoDB Atlas on GCP。除了想確保營運上的彈性，避免侷限在單一公有雲平台之外，WOO Network還看準MongoDB Atlas 可快速擴充、高彈性、易於維運等三大特色。 加密貨幣已成為許多人首選的投資標的，其市場變化非常快速，很可能在短時間內有眾多用戶上線交易，MongoDB Atlas的Auto scaling功能，可依照預先設定快速增加儲存空間、處理器、記憶體等資源，確保整體交易的順暢性，而且在資源擴充期間不會影響到服務運作流程，有助於WOO X平台維持穩定運作。 而 MongoDB 的分散式架構 Sharding 分片，有助於 Woo X平台輕易的大量儲存使用者的歷史數據，並且支援大量歷史交易紀錄與歷程的分析與運算，實現更多分析應用的服務。 最後，MongoDB Atlas支援市面上各種資料庫品牌，擁有相容多種資料格式的彈性設計，非常適合收集不同格式資料與後續分析之用，有助於WOO X平台提供用戶期待的即時線上分析功能。此外，MongoDB Atlas內建易於使用的管理工具，管理團隊可快速掌握系統的運作狀況、效能等資訊，並在發生異常事件前主動掌握與解決，大大降低維運團隊的負擔。 林宣丞說，無論開發或維運團隊的工作都非常繁重，需要一套高穩定、易於操作的NoSQL資料庫方案，才能讓他們專注自身的工作。MongoDB Atlas在全球市場累積非常多成功案例，可靠度與穩定性等絕對毋庸置疑。尤其，MongoDB 技術團隊在專案啟動前、中、後等階段，都提供非常完善的協助，讓我們能順利將非交易相關資料逐步轉移到MongoDB Atlas on GCP平台，對提升WOO X平台效率帶來很大幫助。 展望未來 持續擴大 MongoDB Atlas應用場景 維持WOO X平台市場領導地位 在兼顧資料保密性與使用者體驗等多種因素下，目前WOO Network選擇將MongoDB Atlas應用於WOO X平台上的Various Data 、Market Data 、Data Analysis 、Number等四大領域。Various Data主要負責各種文件、API介面等資料收集， Market Data則可提供市場的即時資訊、超巨量資料等。資料分析則用於查詢最佳化、虛擬化等部分。Number部分則用於儲存大量數字，提供簡單存取服務等工作。 自從引進MongoDB Atlas之後，WOO X平台得以維持絕佳效能狀況，除了可進一步提供用戶更多元化的資料，以及穩定、可靠的使用者介面外，後台開發團隊及DevOps團隊亦獲得極大效益。開發團隊表示，MongoDB Atlas協助他們大幅縮短專案開發時間，更可依照市場需求快速推出新功能。DevOps團隊則指出，MongoDB Atlas的自動備份、監控等功能非常強大，且在部署上也非常方便，大大縮短後續維運時間。 WOO Network將會持續評估MongoDB Atlas， 尋找更多合適的應用場景，務求為消費者提供更多元化的服務。 「引進MongoDB Atlas之後，我們順利解決過往面對的效能、維運等挑戰，讓我們專注為用戶提供即時的市場動態和交易資料等資訊，對提升WOO X平台競爭力有極大幫助。未來，我們會持續跟MongoDB深入合作，讓用戶享受到更好的加密貨幣交易體驗。 」 WOO Network Backend Engineer林宣丞

December 14, 2023
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MongoDB Database Observability: Integrating with Monitoring Tools

This post is the final in a three-part series on leveraging database observability. Welcome back to our series on Leveraging Database Observability! Our previous post showcased a real-world use case highlighting how MongoDB Atlas’s observability tools effectively tackle database performance challenges. Whether you’re a developer, DBA, or DevOps engineer, our mission is to empower you to harness the full potential of your data through our observability suite . Integrating Atlas metrics with your central enterprise observability tools can simplify your operations. By seamlessly working with popular observability tools, our approach helps teams streamline workflows and enhance visibility across systems. Integrating MongoDB Atlas with third-party monitoring tools MongoDB’s developer data platform combines all essential data services for building modern applications within a unified experience. Our purpose-built observability tools for Atlas environments offer automatic monitoring and optimization, guiding diagnostics tailored specifically for MongoDB. Additionally, we extend Atlas metrics into your existing enterprise observability stack, enabling seamless integration without replacing your current tools. This creates a consolidated, single-pane view that unifies Atlas telemetry with other tech and application metrics, ensuring comprehensive visibility into both database and full-stack performance. This integration empowers you to monitor, receive alerts, and make data-driven decisions within your existing workflows, driving greater efficiency. Below is a quick guide to modifying integration settings through the Atlas UI and the popular integrations we support: Navigate to the Project Integrations page in Atlas. Choose the organization and project you want to configure from the navigation bar. On the Project Integrations page, select the third-party services you’d like to integrate. Configure the chosen services with the required API keys and regions. Critical integrations for your observability platform With Atlas’s Datadog and Prometheus integrations, you can send critical MongoDB metrics to these platforms, empowering detailed, real-time monitoring. Through Datadog , you can track database operation counts, query efficiency, and resource usage, ideal for pinpointing bottlenecks and managing resources. Similarly, Prometheus enables you to monitor essential metrics like query times, connection rates, and memory usage, supporting flexible tracking of database health and performance. Both integrations facilitate proactive detection of issues, alert configuration for resource thresholds, and a cohesive view of Atlas data when visualized in Grafana. Atlas’s integration with PagerDuty streamlines incident management by sending metrics like performance alerts, billing anomalies, and security events directly to PagerDuty. This integration records incidents automatically, notifies teams upon alerts, and supports two-way syncing, ensuring resolved alerts in Atlas are reflected in PagerDuty. It enables efficient incident response and resource allocation to maintain system stability. With Atlas integrations for Microsoft Teams and Slack, you can route key metrics—such as query latency, disk usage, and throughput—to these channels for timely updates. Teams can use these insights for real-time performance monitoring, incident response, and collaboration. Notifications through these platforms ensure your team stays informed on database performance, storage health, and user activity changes as they occur. Use case: Centralized observability with MongoDB Atlas, Datadog, and Slack Let’s walk through a hypothetical scenario for ShopSmart, an e-commerce company that leverages MongoDB Atlas to manage its product catalog and customer data. As traffic surges, the DevOps team faces challenges in monitoring application performance and database health effectively. To tackle these challenges, the team leverages MongoDB Atlas’ integration with Datadog and Slack, creating a powerful observability ecosystem. Integrating MongoDB Atlas with Datadog: The team pushes key MongoDB Atlas metrics into Datadog, such as query performance, connection counts, and Atlas Vector Search metrics. With Datadog, they can visualize these metrics and correlate overall MongoDB performance with their other applications. Out-of-the-box monitors and dedicated dashboards allow the team to track metrics like throughput, average read/write latency, and current connections. This visibility helps pinpoint bottlenecks in real time, ensuring optimal database performance and improving overall application responsiveness. Setting up alerts in Datadog: The team configures alerts for critical metrics like high query latency and increased error rates. When thresholds are breached, Datadog instantly notifies the team. This proactive approach allows the team to address potential performance issues before they impact customers. Integrating Datadog with Slack: To ensure fast communication, alerts are sent directly to the dedicated Slack channel, “ShopSmart-Alerts.” This integration fosters seamless collaboration, enabling the team to discuss and resolve issues in real-time. With these integrations, ShopSmart’s engineering team can monitor performance quickly and address issues efficiently. The unified observability approach enhances operational efficiency, improves the customer experience, and supports ShopSmart’s competitive edge in the e-commerce industry. By leveraging MongoDB Atlas, Datadog, and Slack, the team ensures scalable performance and drives continuous innovation. Conclusion MongoDB Atlas empowers developers and organizations to achieve unparalleled observability and control over their database environments. By seamlessly integrating with central enterprise observability tools, Atlas enhances your ability to monitor performance metrics and ensures you can do so within your existing workflows. This means you can focus on building modern applications confidently, knowing you have the insights and alerts necessary to maintain optimal performance. Embrace the power of MongoDB Atlas and transform your approach to database management—because your applications can thrive when your data is observable. And that wraps up our Leveraging Database Observability series! We hope you learned something new and found value in these discussions. Sign up for MongoDB Atlas , our cloud database service, to see database observability in action. To dive deeper and expand your knowledge, check out this learning byte for more insights on the MongoDB observability suite and how it can enhance your database performance.

November 14, 2024