{{ ed.h1a }} {{ ed.h1b }}

{{ ed.sub }}

  • Encrypted on the device
  • Append-only history
  • Open export: GraphML, JSON lines
The Vandict Mac app, Logistics workspace: a list of chokepoints and shipping lanes with their status, a 3D globe showing routes and disruptions, and a detail panel for Bab el-Mandeb with traffic figures and sources.

Three things to understand, and how they collide

Most failures don't come from the organisation alone or the world alone. They come from the interaction between the two. Vandict looks at all three.

{{ a.t }}

{{ a.d }}

{{ a.how }}

Does your organisation have enough ways of acting to match everything the world can do to it?

That is the question underneath it all. Using the Viable System Model, Vandict looks at whether an organisation has the possible states it needs (ways of doing things, resources, information flows and decisions) and compares that space of possibilities with the space of possibilities in its environment.

What makes a situation hard to read

Complex systems share a set of characteristics, from adaptation and emergence to path dependence and nonlinearity. For anyone trying to make decisions inside one, they show up as three challenges for data, decision-making and management.

Together these make up observer complexity: what Vandict measures in organisations that face volatile environments.

AdaptationCo-evolutionDiversityNonlinearitySelf-organisationEmergencePattern formationPath dependenceBifurcation & sensitivityDissipative structuresMultiscale interactionsSpace of possibilities Space of possibilitiesThe possible things that could happenCounterintuitivenessEffects run against intuitionUncertaintyFutures diverge quickly

Hover or tab to a characteristic or a challenge to trace its links.

Twelve characteristics of complex systems drive three challenges for the observer:

Space of possibilities

Diversity, Self-organisation, Emergence, Bifurcation & sensitivity, Multiscale interactions, Space of possibilities

Counterintuitiveness

Adaptation, Co-evolution, Diversity, Nonlinearity, Self-organisation, Path dependence, Dissipative structures, Multiscale interactions

Uncertainty

Co-evolution, Nonlinearity, Emergence, Pattern formation, Path dependence, Bifurcation & sensitivity, Dissipative structures, Multiscale interactions, Space of possibilities

{{ c.t }}

{{ c.d }}

Helmand, 2006–2014: a war as an agent-based model

One of the models this approach can produce. About 5,300 simulated people across 14 districts choose what to do week by week, through eight years of a real war. The model shows the possible situations, not a single forecast, and measures all three challenges.

The same method applies to charities, defence and companies working in highly volatile environments.

Helmand model, Province map: villages coloured by violence, links between villages, and real operations on a 2006 to 2014 timeline.
{{ m.k }} {{ m.v }}

{{ m.d }}

See what's built and where it's going.

A 45-minute walkthrough for investors, design partners and customers.

Request a briefing

How Vandict works

Four methods cover the organisation, its environment and the interactions between them. They sit on five layers, built from the core outwards. Each is labelled built, next or planned.

{{ m.no }}{{ m.s }}

{{ m.t }}

{{ m.d }}

  1. {{ l.no }}
    {{ l.status }}

    {{ l.layer }}

    {{ l.rem }}

The ontology core

A native Mac app with an encrypted, append-only store at its centre. 126 core tests pass, including a hardware Secure Enclave round trip.

{{ g.t }}

{{ g.d }}

Where it goes next

Four phases, from foundations to defence-ready.

View the roadmap

Helmand Insurgency ABM

An agent-based model of Helmand province through the 2006–2014 war. About 5,300 people in 14 districts each choose behaviours week by week, from farming and trading to the opium economy, coercion and lethal violence. Nothing in the patterns below was coded in; they emerge from people interacting.

{{ mtab.alt }}

{{ mtab.title }}

{{ mtab.d }}

Complexity claimed by measurement, not assertion

Each observer-complexity challenge is measured in the model, so its effect on decisions can be seen rather than argued.

{{ m.k }}

{{ m.q }}

{{ m.v }}

{{ m.long }}

{{ e.t }}

{{ e.d }}

Method, from the model: one instrumented province run, 2006–2014. Figures come from an illustrative seed, not the publication seed-average. The Complexity and Complexity II tabs use different engine settings, so some figures differ between them.

A model for your situation

Charities, defence and companies in volatile environments: see what a model of your world could show.

Request a briefing

Four phases

Each phase earns the next. The plan widens only once the previous step works for real users.

  1. Phase {{ ph.no }}{{ ph.s }}

    {{ ph.t }}

    {{ ph.d }}

Talk through the plan

We'll walk through what's built and what each phase needs.

Request a briefing

Two editions, one platform

Both editions share the same encrypted, append-only core. They differ in who they serve and what they model. Each row says what is built and what is still to come.

Feature Proelium Mercator {{ c.k }} {{ c.mil }} {{ c.civ }} Next step Request a Proelium briefing Request a Mercator briefing

See what's built and where it's going.

For investors, prospective design partners and future customers. Tell us which you are and we'll shape the conversation around it.

  1. 01We reply within one working day.
  2. 02A 45-minute walkthrough of the ontology core and the roadmap.

Request a briefing

I'm interested as
{{ errName }}
{{ errOrg }}
{{ errEmail }}

We only use these details to reply to you.

Request received

{{ sentMsg }}

Straight answers

{{ q.q }}

{{ q.a }}