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Resources · Use Cases

Use Cases

The challenge, the approach, and the results for each Predictim product, step by step.

Aerial view of a container terminal
USE CASES
Featured
Composite scenario · real published metrics
Aerial view of an automotive manufacturing assembly line floor
USE CASE / SEMANTIC MIDDLEWARE
Cross-domain disruption response

Cutting the disruption-to-decision gap from 15 minutes to 2

When a disruption — a machine fault, a delayed crew, an unavailable resource — only exists as a line in a shift log or a verbal handover, someone has to notice it, interpret it, and manually update the schedule. That translation step is usually the slowest part of the response, and it repeats independently in every scheduling domain a business runs: production, transport, projects, staffing.

99.7% Semantic alignment accuracy88.2% Hallucination catch rate15 min → 2 min Decision latency
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Two nurses at a hospital ward station at night, one checking a staff roster on screen while the other takes a phone call
USE CASE / HEALTHCARE ROSTERING
Hospital nurse rostering

Turning “off sick tonight” into an updated nurse roster

99.7% Semantic alignment accuracy98.0% vs 79.5% Correct response chosen, planner + GenOR-Twin vs alone88.2% Hallucination catch rate
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A line of white semi-trucks driving along a highway at sunset
USE CASE / FLEET ROUTING
Delivery and freight fleets

Re-planning routes from what drivers actually report

+3.7% Objective vs rule-based pipeline (Solomon R101)82% Real-log phrasings a rule-based parser missed~2 ms Semantic inference time, any network size
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Aerial view of a railway line running straight through dense forest
USE CASE / MEGAPROJECT RISK
Infrastructure and megaproject risk

A cost contingency you can defend when the risk assessments disagree

258 Real megaprojects in the reference set83 pp Rail shortfall of zero-contingency planning96 / 50 pp Fixed-link / road shortfall
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Looking up between night-time office towers, with a green and red market ticker running down one facade
USE CASE / INVESTMENT RISK
Quant funds and systematic asset managers

When the consensus says 0.25%, and one claim says otherwise

0.25% vs 93.07% Consensus risk vs certified protection25 Real, heavily covered equities validated24.9 pp Average gap to the point estimate (17 equities)
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Aerial view of a shipping container terminal with a gantry crane loading a container ship
USE CASE / PACKING
Multi-site grocery distribution

Cutting damage claims and load time across a multi-site grocery network

+22% Volume utilisation−35% Load time−48% Damage claims
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Aerial view of delivery vans staged in rows at a logistics depot at dawn
USE CASE / ROUTING
Regional last-mile parcel delivery

Holding a 98%+ on-time rate through a mixed van and cargo-bike last-mile fleet

−18% Vehicle-km98.4% On-time rate−24% CO₂ per parcel
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Aerial view of a river basin feeding irrigation canals toward farmland with a city on the horizon
USE CASE / WATER
River-basin water allocation

Arbitrating a dry-season shortage across municipal, agricultural, and industrial demand

< 10 s Sector allocation latency+15% Resource conservation48 h Demand forecast horizon
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Aerial view of offshore wind turbine monopile foundations rising from the sea
USE CASE / CORROSION
Offshore wind corrosion monitoring

Moving from fixed-interval diver inspections to a prioritised risk queue

8.2× ROI Failure prevention rate< 1.2 s Telemetry latency15+ markers Data-points integrated
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Aerial view of a fully loaded container ship departing a port at golden hour
USE CASE / STOWAGE · CONTAINER
Multi-port container stowage planning

Cutting port turnaround time on a multi-port container string

21 Hull stations modelledSOLAS · IMDG Compliance−30% Turnaround time
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Each use case is a composite scenario illustrating Predictim's published product metrics; not a specific client engagement.

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