Data & AI Platform · mongodb.com
MongoDB
92 verified customer use cases (92% with quantified ROI · Avg Value Score 87.3 · 100% with mapped architecture components).
- Verified stories
- 92
- Quantified ROI
- 92%
- Avg value score
- 87.3
- Industries served
- 12
- Distinct products
- 62
MongoDB Sample Archived · Aug 29, 2025 Avila Avila needed to transform fragmented grant documents and opportunity sources into a structured, searchable system that could help public-sector and nonprofit users find, understand, and draft grant applications faster. 100,000 grant opportunities indexed Anthropic · MongoDB Atlas · MongoDB Atlas Search MongoDB Sample Archived · Aug 11, 2025 Workleap Workleap wanted to embed generative AI across its HR and talent-management suite without stitching together separate third-party tools for vector search, full-text search, filtering, and cross-product data retrieval. The company migrated to Atlas as its foundational database in 2014. MongoDB Atlas · MongoDB Atlas Search · MongoDB Vector Search MongoDB Sample Archived · Jul 29, 2025 CrowdSec CrowdSec needed a more agile data platform than PostgreSQL so it could evolve threat-intelligence schemas quickly, avoid downtime-heavy upgrades, and turn growing cyber-threat telemetry into searchable and AI-ready… CrowdSec has more than 110,000 live engines sending data regularly. MongoDB Atlas · MongoDB Atlas Search · MongoDB Atlas Vector Search MongoDB Sample Archived · Jul 27, 2025 ArcelorMittal ArcelorMittal needed to unify scattered quality data across global factories to reduce defects, cut costs, and ensure customer satisfaction in a complex steel production process. ArcelorMittal chose MongoDB Atlas on Azure to power E-GPQS, enabling scalable, low-maintenance data processing… MongoDB Atlas MongoDB Sample Archived · Jul 16, 2025 CentralReach CentralReach needed a flexible clinical data platform that could unify billions of heterogeneous records, reduce administrative burden on autism-care teams, and support natural-language retrieval over patient… CentralReach processes approximately 62 million service appointments per year. LlamaIndex · MongoDB Atlas · MongoDB Atlas Vector Search MongoDB Sample Archived · Jun 18, 2025 Base39 Base39 needed to replace slow, subjective credit analysis workflows that could take up to 10 days and required specialist intervention to adapt machine learning models to new data sources. Base39 cut loan analysis costs by 96% and reduced infrastructure expenses by 84%. Amazon Bedrock · Claude 3.5 Haiku · Claude 3.7 Sonnet MongoDB Sample Archived · Jun 18, 2025 Amadeus Amadeus needed a faster, more intelligent way to investigate recurring IT issues across vast volumes of system logs from millions of daily transactions. Additionally, it saw a turnover of more than €5 billion in 2024. MongoDB Atlas · MongoDB Atlas Search · MongoDB Atlas Vector Search MongoDB Sample Archived · Jun 18, 2025 Financial Times FT needed to deliver scalable, hybrid search that blends full-text precision and AI driven semantic discovery across more than a million daily search queries, maintaining performance and relevance at scale. LG U+ Read about how LG U+ improves efficiency by 30% with MongoDB-powered AI tool DevRev Learn how IT company… MongoDB Atlas · MongoDB Atlas Search · MongoDB Atlas Vector Search MongoDB Sample Archived · Jun 18, 2025 Huntr Huntr needed to replace Elasticsearch so its small engineering team could deliver reliable search across a rapidly growing job database, support global location-based discovery, and create headroom for new AI-driven… Huntr automatically generates job boards for over 150 major cities worldwide. MongoDB Atlas · MongoDB Atlas Search MongoDB Sample Archived · Jun 18, 2025 Fireworks AI Fireworks AI needed a vector database that could supply grounded enterprise context to generative AI models, reduce hallucinations, support customer-controlled deployments, and avoid forcing sensitive data into… Fireworks AI curates, optimizes, and deploys over 40 different AI models. MongoDB Atlas · MongoDB Atlas Vector Search MongoDB Sample Jun 17, 2025 SIDIS SIDIS needed a data platform that could unify structured and unstructured data from hundreds of sources, support hybrid cloud and on-premises deployments for regulated customers, and keep pace with transaction growth… A key report expanded from around 8,000 accounts to 18 million accounts and is now available in seconds instead… MongoDB Advanced Enterprise · MongoDB Atlas MongoDB Sample Jun 17, 2025 Syncly Syncly needed a more efficient way to run semantic analytics on voice-of-customer data as its user base and embedding volumes grew beyond what manual similarity calculations could support. “If we had to go through more than 10,000 similarity comparisons for a feedback analysis, we can now get the… Atlas Vector Search · MongoDB Atlas MongoDB Sample Jun 12, 2025 Stax.ai Stax.ai needed to tame fragmented unstructured retirement-plan data and replace slow manual document handling that could not scale across thousands of plans. Google Cloud enabled high-performance processing of tens of thousands of documents each day. Google Cloud · MongoDB Atlas MongoDB Sample May 28, 2025 Occidental Petroleum Occidental Petroleum needed to avoid an expensive, lengthy manual review of 1.5 million lease documents and create a scalable way to classify and extract metadata from millions of PDFs. Atlas Vector Search achieved retrieval times of less than 200 milliseconds across more than 100 GB of text. AWS Lambda · Amazon S3 · Microsoft Azure AI Document Intelligence MongoDB Sample May 28, 2025 Major Canadian bank A major Canadian bank needed to unify fragmented capital-markets data spread across dozens of applications and domains so teams could stop duplicating information and start producing trusted analytics and AI-driven… The bank’s IT team oversaw 76 applications and 113 data domains in the Capital Markets division. Databricks · MongoDB Atlas · MongoDB Enterprise Advanced MongoDB Sample May 26, 2025 Monoprix The best-suited solution TOL tackles multiple challenges, including the need for easy processing of various types of documents and the need to email each customer their receipt before they leave the store. An early start In 2021 Monoprix began designing its initial solution for digitizing receipts based on… MongoDB Atlas MongoDB Sample May 23, 2025 Novo Nordisk Novo Nordisk needed to shorten the slow and error-prone process for producing clinical study reports while keeping document generation deterministic and regulator-friendly in a tightly controlled pharmaceutical… "MongoDB has helped us cut writing times by 90%" MongoDB Atlas MongoDB Sample Archived · May 23, 2025 FAIRTIQ FAIRTIQ needed a scalable, high-availability backend to process 320k+ trips/day across six countries, ensure near-zero downtime, support rapid growth, and handle noisy GPS-based data accounting. Currently FAIRTIQ processes 320,000 trips daily and is available in eight European countries where it’s used… MongoDB Atlas · MongoDB Atlas Data Federation MongoDB Sample May 19, 2025 Naologic Naologic needed to build AI-powered ERP applications quickly while avoiding rigid schemas, duplicated search infrastructure, and repeated data remodeling whenever customers connected new internal or external business… Naologic started working on the platform three years ago. MongoDB Atlas · MongoDB Atlas Vector Search MongoDB Sample May 19, 2025 Ignition Ignition needed to automate the go-to-market lifecycle and support retrieval-augmented generation without keeping operational data and vector indexes in separate systems that were harder to synchronize and slower to… "You can literally take a process that takes almost 90 days, like a product launch process, and then get it… MongoDB Atlas · MongoDB Atlas Vector Search MongoDB Sample Apr 30, 2025 Questflow Our vision is to create a new way of working in the future.” Bob Xu Co-founder and CEO, Questflow THE CHALLENGE Building personalized and dynamic AI agents In the era of AI, having AI agents is now a trend. MongoDB Atlas · MongoDB Atlas Vector Search MongoDB Sample Apr 25, 2025 SiCepat Ekspres SiCepat Ekspres needed to replace a monolithic SQL Server logistics platform that struggled with real-time order and delivery data as Indonesia’s e-commerce growth drove a rapid increase in package volume. Processing time was reduced by more than 98% from three hours to around two minutes. MongoDB Atlas · MongoDB Atlas Online Archive · MongoDB Realm MongoDB Sample Apr 25, 2025 One AI “They are spread across use cases in multiple domains, from analyzing financial documents to AI-automated video editing.” THE CHALLENGE Focus on what you do best One AI’s main objective as a platform is to use AI to… One AI Talk to an Expert One AI brings language-based AI to over 150 million documents worldwide Innovative… MongoDB Atlas MongoDB Sample Apr 25, 2025 Relevance AI Relevance AI Talk to an Expert Relevance AI agents deliver 3,000% ROI for clients with MongoDB Industry Transportation & Logistics Product Atlas Vector Search MongoDB Atlas Use Case Logistics Optimization THE CHALLENGE… “A typical AI agent that’s running well can deliver an ROI of around 3,000% for the customer,” said Koh. MongoDB Atlas · MongoDB Atlas Vector Search