USE CASES
Four decisions, run live on real data
Every journey below runs against real public or synthetic datasets, not a mockup. No client names or client data appear here.
RETAIL & DISTRIBUTION, FMCG, CONSUMER GOODS, WHOLESALE
Reorder Desk
Supply chain directors, demand planners, S&OP leads
2,000 rows of real SKU-level sell-out data
The pain
A weekly reorder decision that lives in a spreadsheet, slow and blind to lead-time changes until it is too late.
How it runs
Sell-out data, a monthly demand aggregate, a 3-month forecast, and a reorder plan, written straight to the planning warehouse.
See what happens to your reorder quantities when supplier lead time changes, on your own numbers, in minutes.
BANKING, TELCO, INSURANCE, UTILITIES, SUBSCRIPTION
Save Desk
Retention leads, marketing ops, and their DPO
45,211 real banking-customer records, PII-enriched
The pain
A churn score nobody turns into a next action, because legal blocks any AI that touches customer data.
How it runs
Customer data is scanned and masked for PII before a churn model or an AI agent ever sees it, then the top at-risk accounts get a drafted retention offer.
An AI that drafts the outreach for your most at-risk customers, after their personal data has already been scanned and masked.
MANUFACTURING, ENERGY & INDUSTRIALS, LOGISTICS
Supply Risk Report
COOs, plant and site managers, supply risk owners
120 assets, 10,000 sensor readings, cross-system join
The pain
A risk picture split across machine health, demand, and a vendor's emailed spreadsheet, none of it talking to the others.
How it runs
Factory asset health, sell-out data, and vendor sensor files fan into a single risk score per site.
Your machine data, your sales data, and the spreadsheet your vendor emails you, joined into one risk report automatically.
BANKS, FINTECH, PAYMENTS, INSURANCE
Fraud Model Scorecard
Fraud and risk teams, model-governance owners
20,000 payment transactions with fraud labels
The pain
A model that quietly degrades in production, and a scorecard that flatters instead of reporting honestly.
How it runs
Every run re-scores the model against a held-out slice it has never seen, and reports precision honestly next to a baseline.
An assert gate that refuses to publish a scorecard that quietly got worse.
Bring your own decision
Reorder, retention, risk, or fraud, we'll show it running on OpticIQ.
Request demo