DECISION INTELLIGENCE

    Dashboards tell you what happened. AIS tells you what to do about it.

    AIS is the Automated Intelligence System built by Beyond Data. It grounds AI in an ontology of your operation: trucks, crushers, work orders, and sites become navigable objects with definitions, relationships, and full history. Every answer, alert, and recommendation traces back to the evidence behind it, so AI stops being a black box and becomes something your team can rely on. AIS runs your whole intelligence loop: notice what's happening, explain it, anticipate what's next, recommend what to do, and learn from what happened.

    Is This For You?

    Honest fit, before we both commit.

    This is for you if…

    • You run a heavy asset operation: mining, transport, logistics, agriculture, or utilities, roughly $50M to $500M revenue
    • Your operations managers reconcile three spreadsheets to work out what needs attention today
    • You want AI in your operation, but only if every answer can be explained and every recommendation traced to evidence
    • You believe your team have expert knowledge, and you want to capture and compound that knowledge, so you can be more efficient year after year

    This probably isn't the right fit if…

    • You need data unification and analytics first. Start with the AgileData platform
    • You want AI that silently takes actions in your systems from day one. AIS recommends and audits; your people approve
    • Your operation runs fine on gut feel and you're not ready to change how decisions get made
    What You Get

    Four concrete deliverables.

    Your operation as navigable objects

    An ontology turns raw operational data into the things you actually run: trucks, crushers, work orders, sites. Each one carries its definition, its relationships, its trust state, and its full timeline. When someone asks "why did availability dip in May?", they click from the number straight to the objects and evidence behind it.

    AI that's grounded, not guessing

    Every AI answer and agent in AIS reads through the ontology, never around it. Semantic context means the AI knows what your terms actually mean; full decision traceback means every output can be walked back to source. Reliable and transparent, by construction.

    Attention and recommendations, routed to the right person

    AIS watches your operation against rules you can read and audit. When something needs attention, it reaches the person whose job it is, with the evidence and a recommended action attached. Your people approve, adjust, or reject. Thresholds are governed per site, so the system earns trust instead of crying wolf.

    Institutional memory that compounds

    Every recommendation, the reasoning behind it, the decision your expert made, and the eventual outcome is recorded in the decision ledger. Your team's judgment stops walking out the door and starts making next year's decisions faster and better than this year's.

    How it works

    The intelligence loop

    Business intelligence isn't a stack of reports. It's a loop: perceive what's happening, understand why, predict what's next, decide what to do, act on it, and learn from the outcome, with the right people coordinated at every step. Most tools park at understanding; the dashboard renders and the loop stops. AIS is built to close the loop, and every stage you move up it compounds: better perception makes explanations sharper, explained decisions make predictions testable, and recorded outcomes make every future recommendation smarter.

    1. 1

      Perceive

      Rules you can read and audit watch every source. Problems surface as events with evidence, not as a number that quietly moved.

    2. 2

      Understand

      Every metric explains itself: definition, source, freshness, and a trace back through the objects and events behind it.

    3. 3

      Predict

      Forecasts and scenarios run against the same definitions, so you can test a decision before you commit to it.

    4. 4

      Decide

      Trade-offs are weighed against your rules and a recommendation lands in the queue with its reasoning attached.

    5. 5

      Act

      Your people approve and act in their own systems. AIS records what was decided, by whom, and on what evidence.

    6. 6

      Learn

      Outcomes are measured against what was recommended, so the next call is better informed than the last one.

    And back to perceive, better informed than the last cycle.

    Coordinate runs across all six. Whatever the system notices, it reaches the person whose job it is, with the evidence attached.

    How We Work

    Senior-led. Outcome-first. No scoping theatre.

    We model your first operational domain, stand up your first apps inside your environment, and switch on the loop: monitoring, recommendations, and the decision ledger. From there, each domain we add makes the next one faster.

    Managed deployment

    Typical Duration

    Senior-led, in your environment

    Engagement Model

    Senior AI consultants

    Team

    Brisbane + remote

    Delivery

    Outcomes You Can Expect

    What changes after the engagement.

    Questions answered with evidence

    In a quarterly review, "why did availability dip in May?" is answered by clicking from the metric to the objects and events behind it. No analyst queue, no reconciliation exercise.

    Problems caught before they're breakdowns

    An alert leads through an object to evidence, and an intervention pre-empts a failure. The "how did it know that?" moment is the product working as designed.

    AI your auditors and your board can live with

    Every output is grounded in governed definitions and traceable to source, and AIS runs inside your own environment, so trust doesn't depend on taking anyone's word for it.

    A business that gets smarter every year

    The decision ledger turns your experts' calls and their outcomes into a queryable operational memory. Efficiency compounds instead of resetting every time someone leaves.

    Common Questions

    Frequently asked.

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