Where the AI runs
On-premise, hybrid or public cloud — recorded per entry. The private-AI axis no hyperscaler directory keeps.
Source-verified register · updated 26 Sept 2026
Proven Use Case Library for Enterprise AI.
Every entry records where the AI actually runs, which regulations touch it, and the source behind the claim — with every figure checked against that source before it publishes.
Unverifiable entries are unpublished, not softened — takedowns land on the register's own ledger.
Register signalslive
Where the AI runs
Regulations tagged in the register
100%of published entries carry a primary source
- Named customer686/686
- Primary source686/686
- Quantified outcome649/686
686 published entriesOpen the register
686published use cases, each linked to its source
30industries covered, from healthcare to logistics
3deployment models recorded per entry, not guessed
tagged per entry, alongside NIS2, DORA and ISO 42001
Latest additions
The newest entries on the register. Each links to the source behind its claims.
Last added
This week+104entries added
This month+393entries added
Personalizing fantasy sports for millions of users
Dream11, the world's largest fantasy sports platform with over 120 million users, used Databricks on AWS to build scalable machine learning capabilities for personalization, social recommendations, real-time predictions and fraud detection. This shortened its time-to-market for new ML-powered solutions by 5x, from 5 months to 4 weeks.
86/100High5 of 7 signalsPrimary source on recordAdded
Dream11Databricks Data + AI Platform · Agent BricksEmpowering marketers with next-gen customer intelligence
Acxiom used the Databricks Data + AI Platform to securely unify customer data for analytics, giving clients the ability to create customer-centric insights, improving marketing conversions and revenue. The platform delivered around 30% faster time-to-market of actionable customer insights and about 15% reduction in operational costs.
86/100High5 of 7 signalsPrimary source on recordAdded
AcxiomDatabricks Data + AI Platform · Delta Lake · Delta SharingNHS England accelerates AI adoption with Microsoft 365 Copilot to improve service delivery and create more time for care
Following the largest healthcare AI trial of its kind globally, which gave more than 30,000 NHS workers across 90 NHS organizations access to Microsoft 365 Copilot and found it saved an average of 43 minutes per staff member per day on administrative tasks (about five weeks per person annually), NHS England is rolling out Microsoft 365 Copilot to 505,000 clinicians and support staff. Ward clerks use it for discharge processes, data analysis, rota building, and bed management; medical secretaries for meeting minutes and templates; and HR, finance, and procurement teams for core administrative functions. The agreement also gives NHS organizations access to Copilot Studio, letting NHS England build agents centrally and individual trusts build custom agents for tasks like reducing help desk burden or accelerating freedom-of-information requests, governed through Agent 365. The deployment follows a 12-month onboarding plan with 200,000 users targeted within the first six months.
86/100High5 of 7 signalsPrimary source on recordAdded
NHS England· United KingdomMicrosoft 365 Copilot · Copilot Studio · Agent 365GOSH-led trial of AI-scribe technology shows transformative benefits for patients and clinicians across London
A Great Ormond Street Hospital (GOSH)-led, NHS England-sponsored study tested TORTUS, an ambient voice AI-scribing tool, across nine NHS sites in London including hospitals, GP practices, mental health services, and ambulance teams, evaluating over 17,000 patient encounters. The AI listens to consultations and drafts a clinic note and letter in a template personalized to each clinician's style, using generative AI, with clinicians reviewing and editing every note before it is saved to the patient record; the AI performs no clinical decision-making. Results showed a 23.5% increase in direct patient interaction time, an 8.2% reduction in overall appointment length, a 13.4% increase in patients seen per shift in A&E, and a 35% reduction in clinicians feeling overwhelmed by notetaking, with 92% of patients consenting to its use. At St George's University Hospital, time to complete the initial A&E patient note halved; economic modeling by York Health Economics Consortium estimated that national scaling to England's 11,055 A&E clinicians could yield 9,259 extra A&E consultations daily, saving GBP 176 million in documentation time and unlocking GBP 658 million in capacity annually.
86/100High5 of 7 signalsPrimary source on recordAdded
Great Ormond Street Hospital / NHS England· United KingdomTORTUSVxceed builds a near real-time multi-agent AI platform using Amazon Bedrock
Vxceed, a global SaaS provider of AI-powered sales and distribution solutions for consumer packaged goods (CPG) companies, built a multi-agent AI platform on Amazon Bedrock to interpret store-level signals in near real time across traditional trade retail outlets. Specialized agents interpret field signals, summarize patterns, generate narrative explanations, and recommend next steps, and also collaboratively produce short AI-generated video news bulletins (script, audio, and visuals each by a different agent) summarizing daily risks and opportunities. Built with Amazon DynamoDB, AWS AppSync WebSockets, AWS Lambda, and AWS Step Functions, the platform processes about US$250 million in daily transactions for major customers, expanded outlet coverage from 1.6 million to over 2 million stores in 18 months, and delivered 5-10% sales uplift and 15-25% improvement in promotion ROI through earlier issue detection.
86/100High5 of 7 signalsPrimary source on recordAdded
VxceedAmazon Bedrock · Amazon DynamoDB · AWS AppSync +2Coverage by sector
Where the register is deepest today. Every count is the live published set, nothing projected.
Financial Services104
Technology & Software83
Healthcare59
Manufacturing57
Retail56
Energy41
Media & Entertainment39
Government & Public Sector34
Published entries only.
What a hyperscaler directory will not tell you
Four fields we record on every entry. They are the reason a European buyer can shortlist from this register instead of starting a research project.
Which regulations apply
Every entry carries the frameworks that touch it, so a compliance conversation starts from a list instead of a blank page.
How strong the evidence is
Every entry carries a computed 0–100 score in which each point is a named signal on the record. High evidence is unreachable without a primary source and a named customer, and low-evidence entries are hidden until you ask for them.
HighMediumLow
Checked against the source
Every checkable claim is tested against the fetched source, and one unsupported figure fails the whole entry. Nothing publishes on a template, and anything whose source later contradicts it comes down rather than getting softened.
Source-verifiedPublish gate: a passing verification, still matching the entry's content
Shortlist from evidence, not from vendor decks.
Free to browse. Filter by sector, capability and deployment model, and open the source behind any claim.