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AI & Technology

AI meets Operations Research for physical trade.

Falcon combines domain-specific AI, quantitative methods and operational data to support explainable shipping and commodity decisions.

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System architecture

Where the intelligence sits.

The architecture separates language interpretation from calculations and constrained quantitative work, then returns the evidence to a human owner.

  1. Company and market data

    Approved operational, commercial and market context.

  2. Domain intelligence layer

    Retrieval, semantics, documents and domain entities.

  3. AI agent

    Intent, context and tool orchestration.

  4. Quantitative engines

    Calculation, scenarios and constrained optimisation.

  5. Ask Falcon

    Explanation, assumptions and sources.

  6. Human decision

    An accountable person reviews and acts.

Control boundary

A clear separation of responsibilities.

AI interprets context and explains results. The defined quantitative engine performs the calculation or optimisation. A person remains accountable.

  1. AI interpretation

    Understand the question, context and decision boundary.

  2. Quantitative engine

    Solve the defined calculation or constrained problem.

  3. Result

    Return outputs, alternatives and relevant sensitivities.

  4. AI explanation

    Explain assumptions, sources and trade-offs for review.

Trust architecture

Permissions, sources, assumptions and approval.

Enterprise scope is agreed per deployment. Public claims remain bounded by verified product evidence; vendor names, certifications and integrations are not implied here.

Evaluation

Review the architecture against a real workflow.

We normally respond within two business days.

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