Commerce TRIZ Cases

A linked diluent database and API matches scanned products with suitable diluents, usage guidance, and compatibility information.

Temporary impersonation and mirrored SaaS instances help support teams troubleshoot accurately while limiting fraudulent access risks.

Historical tuning data and simulations automate ad scheduling, projecting reach and impressions across managed content networks.

A predictive model forecasts warehouse and delivery staffing, then refines shift plans using performance feedback.

Device usage and transaction histories are combined with recommendation conditions to identify more relevant applications for customers.

Past transaction metrics and machine learning generate verified buyer ratings for faster, platform-agnostic fraud screening.

A recommendation engine uses profiles, feedback, and building identifiers to match products with installation spaces.

The network system prefilters requests using provider location, destination, and deadline to preserve scheduling flexibility.

Biosensors and machine learning personalize checkout interactions in real time.

Live-stream cards add popularity and transfer-volume data for clearer resource choices.

A centralized platform links tee booking, live score tracking, loyalty points, and unified pricing across affiliated golf courses.

Sensors detect item engagement, evaluate spending thresholds, and notify customers before unpurchased goods leave the store.

An automated platform groups users by affinity, divides total costs, and helps suppliers fill shared goods or services.

When users hesitate, the interface recommends a likely selection after inactivity using prior interaction patterns and selective feedback.

An autoregressive neural network and iterative scenarios unify revenue drivers, configurations, and constraints for faster decisions.

This case overlays quick-start and detailed product guidance on live product images, reducing guide switching during operation.

A preprocessing server aligns POS data fields across stores, then aggregates matching item records for unified sales analysis.

Sensors and usage records forecast cartridge depletion, enabling automatic, confirmed, or retail resupply before substance runs out.

A dynamic machine learning model compares nearby order locations, factoring travel time and feedback to reduce shopper waiting.

This case embeds watermarks during NFT minting and uses smart contracts to authorize display while limiting copying and counterfeiting.

This case automates contract generation from software quotes, monitors defined usage conditions, and blocks noncompliant access.

This case uses client imagery and real-time 3D measurements to support remote tailoring and personalized garment fitting.

Tracking and product identifiers pre-verify in-person status, reducing fraud checks while preserving device-based purchasing perks.

Smart shelves, cameras, conveyors, and computerized sacking coordinate item sorting, routing, and real-time inventory updates.

AR guidance helps shoppers find goods faster while rewards support voluntary data sharing.

Customer interaction data and item embeddings personalize offer-page rankings while precomputed features keep display processing fast.

A cloud-controlled interface portion delivers promotions or services while core self-service checkout workflow remains intact.

The server targets terminals from multimedia tags, sets gift validity periods, and upgrades displays by purchase quantity.

This case embeds third-party product details in a child frame, supporting chat, promotions, and purchases without popup disruption.

Historical sales data and neural forecasting refine product scenarios under supply constraints to target revenue.

A vehicle delivery information system displays related products and accepts orders to maintain user expectation during the wait.

Natural language analysis, CRM dashboards, compliance checks, and smart contracts unite engagement insights with royalty distribution.

A returns marketplace sends eligible items from original buyers to new buyers, avoiding restocking and repackaging while reducing emissions.

A proxy agent stores dismissed-ad requests and delivers relevant follow-up content later without requiring personal identifying information.

Browser constraints automate eligibility and secure multiparty funds disbursement.

Automate dealership vehicle offers by matching incentives with live inventory.

Real-time behavior signals and historical patterns adapt website content sequences, reducing trial-and-error navigation.

Ticketed property auctions combine automatic bid extensions, proxy bidding, notifications, and escrow management for clearer transactions.

Manager-verified dish ingredients support precise, personalized nutrition.

The system applies summary guidelines and staged model evaluation to standardize varied transaction descriptions across languages.

Machine learning detects packaging faces, checks image quality, and guides capture before reference-image authentication.

Status-based disclosure helps related users coordinate visits to shared destinations.

User-user interaction scores train contrastive embeddings for precise segments, improving recommendations and reducing computing overhead.

This case links product searches to dynamic user networks for peer knowledge sharing, alerts, polls, and seller feedback.

The case combines mannequin and clothes 3D data, then replaces or blurs facial regions to improve fit identification without eerie imagery.

This case uses tagged action correlations and audio input to execute shopping tasks while providing personalized assistance.

Profile preprocessing, modular scoring, and feedback update experience recommendations while automating task generation and monitoring.

This case uses pre-issued digital certificates and automated verification to improve trust without manual checks for every transaction.

This case uses 3D scans, depth maps, and staged segmentation to place physical objects accurately in immersive AR scenes.

Machine-learning models analyze market, property, and owner data to optimize lease terms and minimize approval risk.