Real problems, AI with context: where the value in data becomes results, by problem and by industry.

Supplier lot, recipe, machine, shift and inspection linked in a graph; models point to the combination that causes the defect before final inspection.

Sensors and work-order history estimate each asset’s probability of failure and remaining useful life.

A graph of product structure, parts, suppliers and customers shows in minutes which products, contracts and stock a change affects.

Tier-2 and tier-3 suppliers and geographic concentration become visible; models estimate delay risk for each critical part.

Models find the process settings that cut energy use without affecting quality.

Manuals, shift reports and work orders become a searchable graph: technicians ask in plain language and get the answer with its source.

Consumption patterns, network topology and inspection history combined prioritize inspections where losses are most likely.

The network graph shows which critical customers, such as hospitals, a fault affects, and which alternative switching is available.

Demand and renewable generation forecast by substation, hours to days ahead, using weather data.

Failure risk multiplied by customer impact to decide where to invest first.

Network, weather, vegetation and past incidents linked to predict where outages will happen.

Every indicator sent to the regulator traces back to its source data; audits take hours, not weeks.

Models relate well and lift parameters to output and recommend adjustments.

Inspections, corrosion, engineering drawings and history linked to each piece of equipment, in a single view of risk.

Compressor and pump failures predicted in time to plan the shutdown.

Near misses, work permits, contractors and shifts linked to identify the conditions that precede incidents.

Who supplies what, for which asset, under which clauses; the impact of a supplier failure becomes clear.

Flaring and emissions forecast and reduced from operating data.

Cycle times, queues and fuel analyzed to predict bottlenecks and reassign the fleet.

Models relate ore characteristics to plant recovery and tune the process.

Activities, contracts, permits and resources in one graph: the knock-on effect of a delay is visible before it happens.

Sensors, inspections and geotechnical models linked; early warnings of abnormal behavior.

Tires and off-road equipment components replaced at the optimal moment, not by calendar.

Environmental conditions linked to assets, deadlines and evidence; none expires without warning.

Feed, environment, genetics and health combined to predict conversion and mortality in protein and aquaculture.

From producer to customer, every lot traced in minutes, for a recall or an export requirement.

Demand and price forecast by export market, with exchange rates and seasonality.

The network of farms, transport and suppliers makes it possible to simulate how an outbreak spreads and prioritize the response.

Slaughter and processing yield by line, with the variables that explain it most.

Each country’s requirements linked to products, plants and certificates: what can ship where.

Weather, traffic and each carrier’s history to predict delays and warn the customer first.

Routes, warehouses, carriers and contracts in one graph; simulate what happens if a node fails.

Freight cost and price forecast by route and season.

The network of carriers, vehicles, accounts and fuel stations reveals fraud rings invisible transaction by transaction.

Maintenance predicted and abnormal fuel use detected by vehicle and driver.

Waybills, invoices, contracts and insurance linked to every trip.

Explainable models show why each customer is likely to leave and which action will keep them.

A fault in a network element instantly shows which services, business customers and SLAs are affected.

Physical, logical and billed inventory reconciled; reveals lost revenue and orphaned assets.

Traffic forecast by cell to invest where demand will be.

Networks of accounts, devices and points of sale reveal SIM-swap and subscription fraud patterns.

Eligibility rules in an ontology: sales agents only offer what is technically possible.

Links between accounts, devices, addresses and beneficiaries expose networks that isolated rules miss.

Models using transaction behavior extend credit at the same level of risk.

Entity resolution across systems shows each customer’s and group’s relationships and total exposure.

Propensity by customer and channel to offer the right product at the right time.

Every figure in a central bank report traceable back to the original transaction.

Who to contact, when, through which channel and with which offer, based on the customer’s profile and relationships.

Linking repair shops, providers, policyholders and witnesses reveals recurring schemes.

Models with more variables and interactions price more accurately.

Complexity and cost estimated at first notice: simple cases take a fast track.

What covers what, with which exclusions: service answers based on the actual policy.

Predict who will lapse and act before renewal.

Policies linked to location and physical risk show accumulated exposure to an event.

Compounds, targets, publications and trials linked to surface hypotheses and reuse knowledge.

Predict the sites and patient profiles most likely to recruit on time.

Reports, literature and other sources linked to detect safety signals earlier.

Predict stock-outs and temperature excursions before they compromise the batch.

Predict readmissions, bed occupancy and demand by specialty.

Documents, batches, deviations and corrective actions linked; inspectors find everything with a full trail.

Forecasts that include promotions, weather and local events, to restock what will sell.

Substitutes and complements revealed by real purchases guide assortment and recommendations.

How much each price and promotion really moves, and how much it cannibalizes.

Suppliers, distribution centers and stores linked to predict stock-outs ahead of time.

Each customer’s future value and churn risk to focus loyalty spend.

Attributes, allergens and regulatory requirements by market in one model.

Entity resolution across registries: citizens don’t have to repeat the same information.

Networks of companies, partners, contracts and beneficiaries reveal collusion and conflicts of interest.

Forecast demand for health, education and service desks to allocate staff.

Laws and rules linked to processes: service answers with the legal basis.

Inspect where risk is highest, with explainable criteria.

Assets, incidents and contracts linked to predict failures and plan maintenance.