Hyper-Local AI Travel Marketplace Using Microservices and Semantic Search

Hyper-Local AI Travel Marketplace Using Microservices and Semantic Search | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hyper-Local AI Travel Marketplace Using Microservices and Semantic Search Akshay Sose, Abhay Tagad, Samruddhi Shinde, Yogesh Handge, Sneha Chahande This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8821912/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Modern travel platforms struggle to integrate hyperlocal vendors with global travelers in a scalable and intelligent manner. This paper presents a Hyper-Local AI Travel Marketplace that leverages microservices architecture, semantic search, and artificial intelligence to connect travelers, local vendors, and agencies on a unified digital platform. The system supports realtime bookings, AI-based recommendations, vendor management, and scalable data handling using distributed databases and eventdriven communication. The proposed architecture demonstrates improved flexibility, fault tolerance, and user experience compared to traditional monolithic travel systems. Hyper-local travel Microservices Semantic search AI Travel marketplace Qdrant Cloud-native systems Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8821912","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587719365,"identity":"8214e8ec-0286-49d1-ba22-21caf58984cf","order_by":0,"name":"Akshay Sose","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYDACHgY2KIux8cGHChsw4wCRWpibDWecSQNpaSBWC3ubMG/LYTATrxb+nuPPHvxsq5OTb29sY+BtOG+3tv0w0JYam2hcWiTO9pgb9rYdNjY4c7DtgeSO28nbziQCtRxLy23Apec8D5sEb9uBxA0Sie0GhmduJ5sdAGphbDiMU4v8efZnkn/b6hLnz3/YJpHYdi7Z7PxD/FoMzjaYSfO2MSc23GBskzjYdsDO7AYBWwzPnDGTljkH8ktis2HDmeQEsxtAWxLw+EXuTPozyTdloBA7/vDxnwo7e7Pz6Q8ffKixwe19EGBkQ7ATwSoT8CkHgz8Ipj1BxaNgFIyCUTDiAAASC2uDh6RrdQAAAABJRU5ErkJggg==","orcid":"","institution":"SCTR’s Pune Institute of Computer Engineering (PICT)","correspondingAuthor":true,"prefix":"","firstName":"Akshay","middleName":"","lastName":"Sose","suffix":""},{"id":587719430,"identity":"8c180f91-3f7a-40a5-a7d8-f1a04043ee3b","order_by":1,"name":"Abhay Tagad","email":"","orcid":"","institution":"SCTR’s Pune Institute of Computer Engineering (PICT)","correspondingAuthor":false,"prefix":"","firstName":"Abhay","middleName":"","lastName":"Tagad","suffix":""},{"id":587719431,"identity":"843f6ca8-52ef-4551-bb5d-94b0ce45dee0","order_by":2,"name":"Samruddhi Shinde","email":"","orcid":"","institution":"SCTR’s Pune Institute of Computer Engineering (PICT)","correspondingAuthor":false,"prefix":"","firstName":"Samruddhi","middleName":"","lastName":"Shinde","suffix":""},{"id":587719432,"identity":"e7cfad23-4d6c-431d-be16-872aba3cd3b9","order_by":3,"name":"Yogesh Handge","email":"","orcid":"","institution":"SCTR’s Pune Institute of Computer Engineering (PICT)","correspondingAuthor":false,"prefix":"","firstName":"Yogesh","middleName":"","lastName":"Handge","suffix":""},{"id":587719811,"identity":"7417f4f9-6f8b-4567-b828-f2bcc640721e","order_by":4,"name":"Sneha Chahande","email":"","orcid":"","institution":"SCTR’s Pune Institute of Computer Engineering (PICT)","correspondingAuthor":false,"prefix":"","firstName":"Sneha","middleName":"","lastName":"Chahande","suffix":""}],"badges":[],"createdAt":"2026-02-08 13:38:44","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-8821912/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8821912/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102298086,"identity":"d5f5e4b5-d87f-4240-b345-5e304047b92f","added_by":"auto","created_at":"2026-02-10 10:30:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":297762,"visible":true,"origin":"","legend":"","description":"","filename":"Researchpaperonsystemandimplementation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8821912/v1_covered_c8eb9b21-a1ba-404e-87b7-e5f27751ab14.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eHyper-Local AI Travel Marketplace Using Microservices and Semantic Search\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Pune Institute Of Computer Technology","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hyper-local travel, Microservices, Semantic search, AI, Travel marketplace, Qdrant, Cloud-native systems","lastPublishedDoi":"10.21203/rs.3.rs-8821912/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8821912/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eModern travel platforms struggle to integrate hyperlocal vendors with global travelers in a scalable and intelligent manner. This paper presents a Hyper-Local AI Travel Marketplace that leverages microservices architecture, semantic search, and artificial intelligence to connect travelers, local vendors, and agencies on a unified digital platform. The system supports realtime bookings, AI-based recommendations, vendor management, and scalable data handling using distributed databases and eventdriven communication. The proposed architecture demonstrates improved flexibility, fault tolerance, and user experience compared to traditional monolithic travel systems.\u003c/p\u003e","manuscriptTitle":"Hyper-Local AI Travel Marketplace Using Microservices and Semantic Search","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 08:18:39","doi":"10.21203/rs.3.rs-8821912/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d63da3eb-f1e1-4c44-a996-5a5e0583b394","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-10T08:18:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-10 08:18:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8821912","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8821912","identity":"rs-8821912","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}