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    © Quantum Leap, Whiteshield

    Strategic decisions
    need live

    Socio-economic impact analysis for actors and institutions making high-consequence strategic decisions.

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    Scroll to tour the five agent groups
    01AI vision

    The Geospatial Analyst

    How is our territory changing, and where should I act next?

    Infrastructure intelligence powered by sensor fusion.

    The orchestration

    One question.
    Every layer working together.

    In a Workbench, your agents converge. Worker agents build causal models and generate analytics that feed into output agents: reports, dashboards, MCPs.

    Your question

    If tariffs on car exports rise, what happens to my supply chain and revenue?

    Entity data

    01The Geospatial Analyst

    AI vision

    02The Economist

    Socioeconomic impact

    03The Trade Advisor

    Trade

    04The Fiscal Analyst

    Fiscal

    05The Financial Analyst

    FI intelligence

    Reporting

    One synthesis

    Report via email

    Scheduled brief

    Dashboard on LEAP

    Live workbench

    Your AI, via MCP
    • Claude
    • OpenAI
    • Gemini

    Agent groups in Workbenches

    Agents are deployed on workbenches: a set of capabilities, workflows, data layers, and outputs built around one decision domain. There are five groups, and inside them, twenty specialised agents. Each agent pairs an analytical surface with a conversation so users can inspect assumptions, change scenarios, and interrogate the result.
    Workbenches are the analytical surface for agents. A place to run capabilities, build reports and automate insights.
    Causal Impact
    10 nodes · 12 links
    Tidy
    Run model
    Input
    Complete smoking ban starts tomorrow
    1 policy enacted
    Factor
    Effective compliance / enforcement
    0.85 effective ban share
    Factor
    Smoking consumption eliminated
    85% of pre-ban smoking volume
    Output
    Outcome 5: enforcement costs
    150,000,000 USD/year
    Output
    Outcome 1: premature deaths avoided
    2,465 people/year
    Outcomes
    Premature deaths avoided 2,465 people/year · Healthcare costs avoided 442,000,000 USD/year
    You orchestrate

    Teams assemble the workflow, run the relevant agents, and choose the assumptions they want to test. The modelling becomes repeatable instead of manual.

    Leadership consumes

    The result lands where decisions are made: a dashboard, a briefing, an alert, or the assistant the organisation already uses.

    Five groups · Twenty agents

    Five decision domains. Twenty specialised agents.

    The catalogue shows where LEAP can be applied today. Each group is built around one domain, one decision question, and agents that produce visible, interrogable work.

    What will this policy actually do to jobs, health, growth, and the people affected?

    Forecasts, monitors, and simulates the human and economic consequences of a decision, before it is made and after.

    Causal Impact Agent

    A tweakable, node-based theory of change for any intervention, scored across many outcomes.

    A foundation tests the effect of a coding programme for 20,000 students on employment and GDP.

    Public Policy Impact Lab

    Define the KPIs, generate reporting at your cadence, and follow a policy by dashboard or newsletter.

    A government tracks how a plastic ban moves waste and related metrics, without a new study each time.

    Labor Forecasting Agent

    Forecasts future workforce needs under a tested scenario.

    A labour ministry plans reskilling against the projected impact of AI on its workforce.

    Partners

    Built on infrastructure institutions already trust.

    Airbus, NVIDIA, and UP42 extend LEAP's reach across earth observation, accelerated compute, and geospatial data infrastructure.

    Earth observation and satellite infrastructure behind geospatial intelligence.

    Accelerated compute for model execution and AI vision pipelines.

    Geospatial data marketplace for imagery tasking, access, and analysis.

    The governance layer that makes outputs defensible.

    A pipeline can take data, run a model, and return an output. Quantum Governance asks the questions that decide whether the output can survive execution, institutional trust, and public response.
    It encodes the questions a seasoned advisor asks before a decision leaves the room. This is what it means to take the citizen into account: not only the economic mechanics of a policy, but whether it can hold in the world it changes.
    01Is this the optimal policy, or only the obvious one?
    02Will it build or erode leadership's trust and authority?
    03Can the administration actually execute it, given real capacity?
    04Is the narrative right, and through which channels will it land?
    05How will communities receive it, and where might tension rise?

    Three layers working at once. The combination is what makes LEAP defensible.

    01
    The models

    Economic, causal, policy, fiscal, trade, and geospatial models refined over fifteen years.

    02
    The orchestration

    Agents chained into workflows, wired to the data and partners each decision needs.

    03
    Quantum Governance

    How policies connect, and how people receive them. The part nobody else models.

    Models, orchestration, and governance are each useful on their own. The defensibility comes from running them together, grounded in proprietary economic and government-context knowledge.

    Everyone has the models.
    Almost no one has the fifteen years.

    LEAP combines models, agent workflows, partner infrastructure, and the hard-won modelling of how policies connect, whether they will hold, and how people receive them. Governed, auditable, and built to be used again.
    That is the difference between a decision that looks right on a slide and one that survives in the real world.
    Open WorkbenchBack to the top
    Quantum LEAP is a QuantumX product line. NAV is its companion product line for end users.