Snowflake Sample Archived · Aug 5, 2025 Neema A complex multi-system cloud estate slowed analytics delivery, increased maintenance overhead, and made it hard for Neema to innovate quickly on pricing and customer-facing AI use cases. 1,000s of hours saved per year Cortex AI · HubSpot · Mistral 
Capgemini Sample Aug 4, 2025 City of Tampere Tampere wanted to explore generative AI safely and turn that learning into practical internal public-service use cases and governance rather than scattered experimentation. Ask About Procurement Contracts · Ask HR · GPT models 
Infosys Sample Archived · Aug 4, 2025 Financial Times Financial Times needed to support a growing subscriber base and broader product portfolio without overwhelming its service teams, while more than half of incoming cases could potentially be handled through self-service.… 17.4% cancellation-save rate, up from 14% in 2024 as a result of agents having more time to focus on… AI-powered ChatBot with Guided Self-Serve · Einstein for Service · LiveChat (MIAW) 
Salesforce Sample Aug 4, 2025 reMarkable As reMarkable grew in popularity, they started to outgrow their tech stack. reMarkable is a premium, fast-growing company on a mission to help people think better through technology. 21% of customers voluntarily choose Mark over humans Agentforce · Commerce Cloud · Data 360 
Oracle Sample Archived · Aug 3, 2025 Raychem RPG Raychem RPG wanted to triple sales but was constrained by disconnected on-premises systems that slowed quoting, procurement, forecasting, and manufacturing coordination and prevented departments from sharing accurate,… 25% faster response to competitive bids Oracle CPQ · Oracle Customer Experience (CX) · Oracle Fusion Cloud Enterprise Resource Planning (ERP) 
NVIDIA Sample Aug 1, 2025 Nasdaq Nasdaq needed an enterprise AI platform that could search and retrieve business data quickly and accurately for internal and external use cases, but slow embeddings, high latency, rising costs, and accuracy issues… 30% faster response times NVIDIA AI Enterprise · NVIDIA L40 GPUs · NVIDIA NIM 
Confluent Sample Archived · Jul 31, 2025 Wix Wix needed a streaming architecture that could keep up with billions of daily business events, expose fresher analytics to internal and external developers, and eliminate batch and Kafka operations bottlenecks. more than 30 billion daily business events ClickHouse · Confluent Cloud · Confluent Cloud for Apache Flink Salesforce Sample Jul 30, 2025 The Adecco Group Adecco needed to respond to changing candidate expectations and handle high-volume, time-sensitive pre-screening faster, while preserving recruiter involvement and the human element in recruitment. 28 companies successfully fill their vacancies Agentforce 
ServiceNow Sample Archived · Jul 30, 2025 ServiceNow ServiceNow wanted to lower support costs and improve efficiency without losing the personalized, high-touch experience customers expect from human support teams. 37% Of our case workflow is now supported by AI agents AI Agents · Customer Service Management · Knowledge Management Salesforce Sample Jul 30, 2025 Safari365 Safari365 was running a bespoke-travel business on spreadsheets, Word documents, and fragmented tools, which made pricing multi-vendor itineraries, tracking customer context, and removing repetitive advisor work… 3,000 suppliers Agentforce · Agentforce Testing Center · Salesforce 
OpenAI Sample Jul 30, 2025 Intercom Intercom needed a flexible AI platform that could keep pace with rapidly changing models while handling large volumes of customer support interactions, complex workflow tasks, and new voice channels at production… $100 million committed to replatform around AI Fin · Fin Tasks · Fin Voice 
Databricks Sample Jul 30, 2025 Axpo Group But legacy challenges — including data silos, fragmented tools and manual processes — slowed progress. 30% Time savings for power users Agent Bricks Databricks Sample Jul 30, 2025 Adani Digital Labs Adani Digital Labs needed to replace legacy data systems because scaling the Adani OneApp required fresher insights, better governance, and faster iteration on personalized travel and lifestyle services. 20% Databricks Data + AI Platform · Databricks SQL · Delta Lake OpenAI Sample Jul 30, 2025 Blue J Blue J needed to help tax professionals answer complex questions in a regulated domain where research traditionally requires hours, days, or weeks of reading across statutes, rulings, case law, and commentary, and even… 2.7 hours saved per user weekly GPT-4.1 · Retrieval-Augmented Generation (RAG) system 
SLB Sample Jul 29, 2025 Eni Eni wanted to improve drilling efficiency, consistency, and safety in well planning and offshore drilling operations by defining better operating limits and reducing rework, human error, and hazardous rig-floor exposure. 1,224 meters per day DrillOps · DrillPilot · DrillPlan 
IBM Sample Jul 29, 2025 Matrix Renewables Matrix Renewables needed to onboard and monitor a rapidly growing portfolio of solar assets without the delays, data gaps, and scaling limits caused by decentralized monitoring across multiple SCADA systems. 10% reduction in downtime IBM Maximo Renewables 
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 Databricks Sample Jul 29, 2025 SK Shieldus SK Shieldus needed a more scalable analytics foundation because its legacy environment could not support advanced machine learning for proactive security services, dispatch optimization, and customer retention. 6 months Databricks Data + AI Platform · Delta Lake · Lakeflow 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 IBM Sample Jul 23, 2025 Medtronic Medtronic’s teams were spending too much time manually matching invoices, proof-of-delivery documents, and purchase orders, which slowed cash-flow-related processes, introduced errors, and kept staff away from more… Down from up to 20 minutes per invoice to 8 seconds Document Intelligence Platform Accelerator · IBM Consulting for Microsoft · IBM Neudesic IBM Sample Jul 23, 2025 Computer Gross Computer Gross needed to give thousands of B2B ecommerce customers faster product discovery, quoting, and support because its 145,000-product catalog and growing customer base were overwhelming internal teams with… 20% increase in quote-to-order conversion rate IBM watsonx · IBM watsonx Assistant · IBM watsonx.ai Snowflake Sample Archived · Jul 23, 2025 Keywords Studios turn vast but fragmented community, social, review, and video data into timely sentiment insight for game publishers without months of manual analysis. 3 months from AI POC to go-live Cortex AI · Snowflake OpenAI Sample Jul 23, 2025 CNA CNA needed to improve newsroom productivity and investigative reach without compromising public-service standards, because journalists faced labor-intensive reporting tasks while the organization also had to manage… 150 million homes and connected devices ChatGPT · Newsroom Buddy · Parliament AI 
PwC Sample Archived · Jul 22, 2025 unknown An industry-leading healthcare organization had oncology information scattered across siloed records and unstructured notes, which slowed analytics, clinical-trial matching, treatment comparisons and risk detection for… $50M+ in new value potential Google Cloud · Google Cloud Looker · Google Cloud Vertex AI