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 72
Tencent Cloud 29
Oracle 26
EY 18
PwC 16
Confluent 13
DXC 10
BCG 6
Cohere 6 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
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.
10,172 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.