Who it is for
AI strategy, product, architecture, sales and research teams evaluating what has actually been deployed for customers like theirs.
For strategy, product, architecture and go-to-market teams: turn scattered customer stories from Microsoft, Google Cloud, OpenAI, IBM, AWS and more into comparable evidence about the problem solved, what was built, and whether the reported value is credible.
ServiceNow 79
Tencent Cloud 30
Oracle 29
EY 18
PwC 17
Confluent 13
DXC 13
Cohere 7
BCG 6
KPMG 5 The decision problem
Use the library to shortlist relevant deployments, inspect the architecture and outcome, then validate every important fact against its source before applying the pattern to your customer.
AI strategy, product, architecture, sales and research teams evaluating what has actually been deployed for customers like theirs.
Filter by industry or use case, compare customer reference value, inspect the confidence breakdown, and open the cited sources before making a recommendation.
Subscribe to RSS for newly collected stories; the catalog refreshes daily and retains retrieval timestamps.
Latest
KPMG Sample Nov 12, 2026 Undisclosed US retailer A leading US retailer wanted to identify risks such as counterfeit products and litigation before costly incidents occurred. Existing manual reviews and fragmented public data could not reliably surface risks across… More than 55,000 data sources in KPMG Signals Repository AutoML · BERT · BigQuery
ServiceNow Sample Modified · Nov 12, 2026 Medtronic Medtronic employees work under different country, contract, and regulatory arrangements, making a single HR knowledge base insufficient. The company needed a relevant, self-service way to answer routine HR questions and… 200 custom AI use cases in roadmap HRmony · Moveworks · ServiceNow HR Service Delivery
ServiceNow Sample Modified · Nov 12, 2026 Georgia Secretary of State The Georgia Secretary of State needed reliable visibility into poll-pad patch levels and security across 159 counties, as well as a way to identify unknown assets and prioritize vulnerabilities with a small… 10,000 poll pads verified Armis from ServiceNow · Mobile device management solution
ServiceNow Sample Modified · Nov 10, 2026 Copado Copado's growing multi-cloud environment generated thousands of security alerts a day from siloed tools. The security team needed to correlate code, cloud, and infrastructure context, prioritize important… 17K findings remediated in a 30-day window Armis from ServiceNow
KPMG Sample Nov 6, 2026 Fortune 50 healthcare organization A complex post-merger environment left the healthcare organization with an over-customized ServiceNow platform, technical debt, inconsistent processes, and multiple service systems that made support difficult to… 10,000 knowledge articles and 500 catalog items ServiceNow · ServiceNow AI Control Tower · ServiceNow Virtual Agent Auto-Generated Multi-Dimensional Intelligence
Median and 75th-percentile percentage improvements extracted automatically from customer-stated outcomes.
Faster response, processing, turnaround, or deployment times.
Engineering, analyst, or frontline staff hours saved and output gains.
Self-service containment, automated handling, and model precision/accuracy.
Direct operating cost, compute/storage TCO, and financial savings.
Top-line growth, conversion rate, retention, CSAT, and NPS improvements.
Volume of documents, transactions, queries, or users handled at scale.
10,633 mapped deployment components.
AI models and platforms most frequently combined in production.
Methodology
Scores expose the strength and traceability of available evidence, not certainty or guaranteed ROI. A complete first-party source can score well without an artificial multi-source requirement.
New customer stories are picked up from leading cloud and AI vendors every day, newest first.
Claims are linked to named sources, publication dates and retrieval timestamps so provenance stays visible.
Evidence confidence and customer reference value are scored separately with a visible, deterministic rubric.
Use consistent problems, architectures, products and outcomes to find repeatable patterns—not just polished stories.
Search by vendor, industry, use case or product, then compare value, evidence confidence, architecture and source provenance side by side.