→ Entopy is the always-on intelligence layer that helps complex operations anticipate consequence and act earlier.


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Entopy is redefining Unified Intelligence
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Unified Intelligence

Product → 001

Continuously updating operational picture.

Entopy creates a live operational intelligence layer by combining real-time data, targeted predictive models and a continuously evolving world model.

Product → 002

Proactive communication with operators.

The Entopy Operational Agent detects forming operational risks, understands evolving context and proactively communicates with operators.

Product → 003

Scenario analysis and what-if testing.

The Entopy Strategy Agent enables operators to explore scenarios, test interventions and understand operational impact before decisions are made.

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Resources.

Building Unified Intelligence for Complex Operations Ontology Driven AI For Complex Systems Scenario Intelligence At Scale
BLOG ARTICLE

Building Unified Intelligence for Complex Operations

How Entopy’s architecture unifies fragmented data, context, and reasoning to deliver real-time understanding and faster decisions.

Read article
PAPER

Ontology Driven AI For Complex Systems

How semantic operational models improve context awareness and consequence reasoning.

Read paper
PAPER

Scenario Intelligence At Scale

Building operational foresight using AI reasoning and consequence-aware intelligence.

Read paper

Latest news.

Operate ahead of consequence →
Unified Intelligence

Build your intelligence layer.

Harness the future of operational intelligence.

Entopy is the always-on intelligence layer that helps complex operations anticipate consequence and act earlier.

Speak with an expert

Unified Intelligence Platform

Real-time operational intelligence for complex, consequence-aware decisions.

Entopy unifies operational data, predictive models, situational memory and AI reasoning to create a continuously evolving operational picture that helps organisations understand what is changing, what consequences may emerge, and what actions to take.

Product → 001

Continuously updating operational picture.

Entopy creates a live operational intelligence layer by combining real-time data, targeted predictive models and a continuously evolving world model.

Product → 002

Proactive communication with operators.

The Entopy Operational Agent detects forming operational risks, understands evolving context and proactively communicates with operators.

Product → 003

Scenario analysis and what-if testing.

The Entopy Strategy Agent enables operators to explore scenarios, test interventions and understand operational impact before decisions are made.

Building Unified Intelligence for Complex Operations Ontology Driven AI For Complex Systems Scenario Intelligence At Scale
BLOG ARTICLE

Building Unified Intelligence for Complex Operations

How Entopy’s architecture unifies fragmented data, context, and reasoning to deliver real-time understanding and faster decisions.

Read article
PAPER

Ontology Driven AI For Complex Systems

How semantic operational models improve context awareness and consequence reasoning.

Read paper
PAPER

Scenario Intelligence At Scale

Building operational foresight using AI reasoning and consequence-aware intelligence.

Read paper

01 | A continuously updating operational picture.

Inside the system ↘

Data foundation

Real-time and historical data from both internal and external sources is cleansed, standardised, validated and enriched using Entopy core.

Entopy's proprietary synthetic data generation technology enables sparse and incomplete datasets to be improved and rare event data to l be expanded.

Dynamic intelligence network

Many discrete, targeted Al/ML models are deployed to specific areas of the operation, predicting specific dynamics.

Outputs from many micromodels are This enables teams to understand evolving dynamically integrated together with real-time and historical data to create a dynamic network of intelligence.

Challenge

A continuously updated intelligence layer connects data, models and operational context into a shared view of what is happening now.

This enables teams to understand evolving conditions, anticipate change, and act earlier with greater confidence.

02 | Ontology & situational memory.

Inside the system ↘

Ontology

Entopy's proprietary ontology enables dynamic integration and orchestration of data across domains.

The ontology enables data to be attributed to l entities with relationships and rules baked in.

World model

The result is a digital model that reflects the target operation, creating a unique world model.

This gives the system a structured understanding of the operational environment and how its parts relate.

Situational memory

Entopy's ontology is self-adaptive, enabling new facts to be created autonomously.

Situational memories are derived from situation lifecycle monitoring and treated as first-class entities within the ontology, supporting learning and experience within the system over time.

03| Live operational intelligence (Always-on Agent).

Inside the system ↘

Situational lifecycle tracking

An Al agent continuously identifies and tracks emerging situations, monitoring how they evolve, escalate and resolve.

As conditions change, it assesses impact and recommends actions, learning from every outcome to improve future decisions.

Proactive participation

The agent participates in operational workflows in real time, using situational awareness to anticipate, coordinate and optimise responses across stakeholders.

It does this through the distribution of communications through familiar channels as well as following defined escalation paths.

Operational response

Intelligence is translated into timely, practical actions that support teams as situations develop.

This enables operators to respond earlier, coordinate more effectively and improve decisions as conditions change.

04 | Exploratory intelligence (Scenario Agent).

Inside the system ↘

Deep analysis & scenario modelling

A dedicated Al agent for deep analysis uses multi-step reasoning to evaluate situations and test scenarios.

It draws on the full Unified Intelligence layer to deliver insights and outcomes grounded in operational reality.

Wargame & cascading impacts

Built into the agent is a wargaming engine that supports the ability to simulate and test decisions.

Alongside it, a cascading impacts engine evaluates how changes propagate through interconnected entities, constraints and processes.

Decision intelligence

The system translates exploration into clear decision pathways, highlighting trade-offs and likely outcomes.

This enables organisations to pressure-test strategies and act with greater confidence before consequences unfold.

Operate ahead of consequence →
Unified Intelligence

Build your intelligence layer.

Harness the future of operational intelligence.

Entopy is the always-on intelligence layer that helps complex operations anticipate consequence and act earlier.

Speak with an expert

Explore the organisations empowering operations with Unified Intelligence..

Port of Dover Case

Intelligent traffic management.

Earlier insight for live traffic decisions Case Study
Harwich Haven Authority
Harwich Haven Authority Case

Dynamic port resource planning.

Shared intelligence for berth planning Case Study
Fujitsu
Fujitsu Case

Cross-border supply chain intelligence.

Real-time freight visibility and alerts Case Study
Bio Capital Case

Real-time energy optimisation.

Predictive optimisation for energy output Case Study
Glasgow Airport
Glasgow Airport Case →

Passenger movement intelligence.

Predictive insight for passenger flow Case Study
Building Unified Intelligence for Complex Operations Ontology Driven AI For Complex Systems Scenario Intelligence At Scale
BLOG ARTICLE

Building Unified Intelligence for Complex Operations

How Entopy’s architecture unifies fragmented data, context, and reasoning to deliver real-time understanding and faster decisions.

Read article
PAPER

Ontology Driven AI For Complex Systems

How semantic operational models improve context awareness and consequence reasoning.

Read paper
PAPER

Scenario Intelligence At Scale

Building operational foresight using AI reasoning and consequence-aware intelligence.

Read paper
Operate ahead of consequence →
Unified Intelligence

Build your intelligence layer.

Harness the future of operational intelligence.

Entopy is the always-on intelligence layer that helps complex operations anticipate consequence and act earlier.

Speak with an expert

CASE STUDY
Real-time freight visibility, event detection, and sub-second data access across complex supply chains.

Fujitsu transformed cross-border freight visibility with Entopy, enabling real-time event detection and sub-second data access across complex supply chains.

In brief ↘

Challenge

Fujitsu’s Atamai Freight platform needed to unify fragmented, multi-party supply chain data into a single, trusted view.

Siloed systems, dynamic relationships, and limited real-time visibility constrained collaboration and delayed decision-making.

Solution

Entopy deployed an ontology-driven digital twin, structuring data around consignment journeys and linking entities such as consignments, vehicles, ports, and smart seals.

Real-time data ingestion via APIs, combined with targeted capture and segmentation, enabled scalable, secure data sharing across stakeholders.

Unified Intleligence

Entopy’s platform applies intelligent data orchestration and event detection to identify real-time events, such as arrivals, delays, and anomalies, across complex datasets.

This enables predictive insight, automated alerts, and faster, more informed decision-making.

Outcomes ↘
>10
Stakeholder types
<0.2s
Data access via API call
Improved visibility, reduced border processing times
Paul Luckett
Head of Digital Trader Services → Fujitsu Services UK

Working with Entopy has been refreshing. Their platform is supporting some of the fundamental elements of the Atamai Freight service.

CASE STUDY
Discrete model predictions, dynamic orchestration, and proactive communication with operators to support multi-stakeholder ecosystem.

Harwich Haven enabled coordinated decision-making across its port ecosystem with Entopy, optimising vessel scheduling under complex operational constraints.

In brief ↘

Challenge

Harwich Haven operates in a highly constrained environment, where vessel movements are impacted by tidal windows, resource availability, and interdependent schedules.

Limited shared visibility across stakeholders made it difficult to coordinate decisions, leading to inefficiencies, delays, and suboptimal berth utilisation.

Solution

Entopy deployed a digital twin of the port ecosystem, connecting vessel schedules, resource constraints, and operational data into a shared, real-time intelligence layer.

By modelling relationships between vessels, towage, berths, and constraints, the platform enabled stakeholders to identify conflicts early and coordinate optimal sequencing decisions.

Unified Intleligence

Entopy’s platform combines ontology-driven digital twins with interconnected micromodels to model vessels, resources, and constraints in real time.

An intelligent agent, supported by memory, proactively communicates emerging issues and enables rapid scenario testing, allowing stakeholders to evaluate options and coordinate optimal decisions under disruption.

Outcomes ↘
4
Port operational stakeholders
~20%
Improvement to operator response time
Improved cross-ecosystem coordination.

CASE STUDY
Federated micromodel network, real-time data orchestration, and event propagation to support operational decisions under pressure.

Port of Dover reduced traffic congestion with Entopy, enabling predictive decision-making and earlier intervention across one of the UK’s busiest transport routes.

In brief ↘

Challenge

The Port of Dover needed to manage highly variable freight traffic flows, with limited visibility of incoming volumes and congestion risks.

Unpredictable arrivals and external factors (e.g. incidents, weather) created bottlenecks, reducing operational efficiency and increasing disruption across the network.

Solution

Entopy deployed its AI-enabled digital twin platform, combining real-time data with predictive micromodels to forecast freight arrivals and traffic conditions.

The platform provided forward-looking intelligence on volumes and congestion, enabling operators to proactively allocate resources and manage flow.

Unified Intleligence

Entopy’s micromodel architecture chains together discrete models, integrating real-time, event-based data, such as accidents, weather, and network disruptions, to create a continuously adapting traffic model.

This enables dynamic, network-wide forecasting of congestion and freight flows, even under disruption.

Outcomes ↘
25%
Reduction in Transport Access Protocol
30 minute
Improvement to operator response time
Less disruption, better flow, improved awareness.

CASE STUDY
Data-driven modelling, and complex process orchestration, to boost renewable energy production.

Bio Capital increased renewable energy output with Entopy, using real-time AI to optimise biogas production across its UK-wide AD portfolio.

In brief ↘

Challenge

Bio Capital needed to optimise biogas production across multiple AD sites, where performance is driven by complex, interdependent variables such as feedstock and process conditions.

Solution

Entopy deployed its AI-driven data platform to unify operational data across Bio Capital’s AD sites, enabling real-time monitoring and predictive modelling of biogas production.

By combining historical and live data, the platform identifies key performance drivers and supports data-driven optimisation of feedstock and operational strategies.

Unified Intleligence

Entopy’s predictive models analyse large-scale operational data to forecast biogas yields and optimise energy production in real time.

An intuitive, LLM-powered interface enables teams to query data and access insights instantly, making advanced analytics accessible across the business without specialist expertise.

Outcomes ↘
98%
Forecasting accuracy
6-week
Mobilisation time
Improve yield forecasting, reduced feedstock.

CASE STUDY
Multi-step passenger flow prediction, and dynamic forecasting, to support airport operators improve experience.

Glasgow Airport improved passenger flow visibility with Entopy, enabling predictive planning and scenario testing across surface access and terminal operations.

In brief ↘

Challenge

Glasgow Airport needed to manage growing passenger volumes, with limited visibility of how people arrived, moved through the airport, and impacted infrastructure.

Fragmented data and unpredictable demand made it difficult to anticipate congestion and plan operations effectively.

Solution

Entopy deployed an AI-enabled digital twin of passenger movement, modelling journeys from road access through to check-in and security.

By combining historical and live data, the platform provided forward-looking insight into passenger volumes, car park usage, and processing times across the airport.

Unified Intleligence

Entopy’s micromodels simulate passenger behaviour across the airport, predicting arrivals, dwell times, and processing flows in granular time intervals.

Operators can also test future scenarios, such as infrastructure changes or demand spikes, in a virtual environment, enabling proactive planning and optimisation.

Outcomes ↘
94%
Accuracy of traffic flow models
5
passenger journey stages
Improved operational planning & scenario testing.
Jon Matthews
Transformation Director → AGS Airports

We are thrilled to collaborate with Entopy as they bring their cutting-edge digital twin technology to Glasgow Airport. Enhancing passenger experience and operational efficiency is a cornerstone of our vision.

Resources.

Building Unified Intelligence for Complex Operations Ontology Driven AI For Complex Systems Scenario Intelligence At Scale
BLOG ARTICLE

Building Unified Intelligence for Complex Operations

How Entopy’s architecture unifies fragmented data, context, and reasoning to deliver real-time understanding and faster decisions.

Read article
PAPER

Ontology Driven AI For Complex Systems

How semantic operational models improve context awareness and consequence reasoning.

Read paper
PAPER

Scenario Intelligence At Scale

Building operational foresight using AI reasoning and consequence-aware intelligence.

Read paper
An introduction to
Unified Intelligence.
An overview of Unified Intelligence and why it represents a new category.
‘Always-on’
intelligence.
Understanding continuous intelligence and real-time decision-making.
What is
Digital Twin?
A deep dive into Digital Twin and its use in critical infrastructure.
What is
ontology?
Ontology as the foundation of Entopy’s intelligence platform.
AI micromodels
explained.
How AI micromodels enable scalable and composable intelligence.
Synthetic data
generation.
Expanding limited datasets with high-quality synthetic data.
AI
Agent.
An AI Agent designed to support operational decisions and workflows.
Operational
memory.
Persisting system context to inform future decisions.
Cascading impacts
engine.
Modelling how changes propagate across complex systems.

Webcast.

See all webcast

Latest news.

Read all Articles

Operate ahead of consequence →
Unified Intelligence

Build your intelligence layer.

Harness the future of operational intelligence.

Entopy is the always-on intelligence layer that helps complex operations anticipate consequence and act earlier.

Speak with an expert

Case studies

Digital Twin Case Study
Explore resources

Learn more about the Entopy platform.

Resources
View the Entopy platform resources
Digital Twin Software
A solution for the
enterprise, built for scale.
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