Case studies
Illustrative scenarios for governed AI
Fifteen examples of how organizations across industries could approach data and AI work, and how ARCHR would run it.
Illustrative scenario. Based on industry exploration and typical engagement design; not a client result or a guarantee of outcomes.
These are illustrative scenarios across industries, not client results. Each one describes a typical challenge, a sensible way to approach it through Discovery, Pilot, Build and Optimize, the governance questions to settle early, and the qualitative signals a pilot could track. We use scenarios because results depend on each organization's data, systems and rules, and we would rather show our thinking than promise outcomes.
How to read these scenarios
Every scenario follows the same structure: the situation, what the organization wants to achieve, an approach that follows our four phases, technology and governance considerations, and qualitative signals a pilot could track. Each page also includes a simple flow diagram of how data and decisions could move through the solution, and a short list of technology categories that could fit. Cloud options are always AWS, Microsoft Azure or Google Cloud, chosen to fit the organization's existing estate. Regulators named in the scenarios are examples of context from several jurisdictions, not assurance of compliance, and a person stays accountable for every consequential decision.
Financial services
Verification, advice, trading and oversight scenarios for banks, wealth firms, asset managers and fintechs.
Financial services
AI-assisted KYC onboarding: an illustrative scenario
How a financial institution could pair document intelligence with human review to modernize customer verification.
View scenarioWealth management
AI-augmented portfolio monitoring: an illustrative scenario
How a wealth firm could use AI to watch portfolios for drift and risk, and draft client reporting for advisor review.
View scenarioWealth management
AI-assisted advisor call workflows: an illustrative scenario
How a wealth firm could use transcription, summaries and compliance review support to ease the admin that follows client calls.
View scenarioFintech
AI and data governance: an illustrative scenario
How a financial services or fintech organization could build one framework for data, AI and technology risk governance.
View scenarioAsset management
AI-assisted trade cost analysis: an illustrative scenario
How an asset manager could bring pre- and post-trade cost analysis into one governed, explainable workflow.
View scenarioTrading and market making
AI-assisted trade analytics: an illustrative scenario
How a trading business could combine market, order and unstructured data into timely, explainable analytics.
View scenarioTrading and market making
AI-assisted revenue estimation: an illustrative scenario
How a market maker could use trading activity data to estimate revenue earlier and support capital allocation discussions.
View scenarioInsurance
Scenarios for insurers where claims, underwriting and fair treatment of customers come together.
Healthcare
Scenarios for healthcare organizations where privacy is a design constraint from day one.
Retail and consumer
Scenarios for retailers and consumer brands where customer experience and responsible data use go together.
Retail
AI-assisted customer service: an illustrative scenario
How a retailer could use AI to support customers across channels while keeping a clear path to a person.
View scenarioBeverage and alcohol
AI-assisted wine discovery: an illustrative scenario
How a beverage retailer could use AI for personalized recommendations and subscription curation, with responsible-sale controls.
View scenarioManufacturing
Scenarios for manufacturers where uptime, quality and plant safety come first.
Energy, mining and resources
Scenarios for resource operators where safety, asset reliability and remote operations matter.
Public sector and not-for-profit
Scenarios for public bodies and mission-driven organizations with transparency duties and limited budgets.
Public sector
Public-sector service-demand analytics and reporting: an illustrative scenario
How a public body could understand service demand and report on delivery with transparency and privacy built in.
View scenarioNot-for-profit
AI-assisted donor engagement: an illustrative scenario
How a nonprofit could use donor data responsibly to personalize outreach with a small team and limited budget.
View scenarioLet's talk about your data and AI priorities
Tell us what you are trying to solve. We aim to reply within one business day.