VERAIUS
EN TR
Request Demo
Agent Readiness

How ready are you for agents that act?

Most organisations can already run a model. Far fewer can let its output change something without a person retyping it. Twelve questions, about four minutes, and the score is on screen the moment you finish — no form in the way.

Data foundation

An agent cannot act on a number it cannot get, or trust one it cannot trace.

Demand, stock and capacity can be read together for the same period without manual reconciliation.
Key figures have one agreed definition across departments — "on hand" means the same thing everywhere.
Operational data is available at least daily, not as a month-end extract.

Decision clarity

Automation needs a decision with a known owner, a known input set and a known success measure.

The recurring operational decisions are written down, with who makes each one.
For at least one of them, we could state the inputs and the rule a good decision follows.
We measure the outcome of those decisions, not only the activity around them.

Governance and trust

The question is never whether the model is clever. It is who is accountable when it is wrong.

We know which decisions may be automated and which must stay with a person.
An automated action would be logged with its reasoning, its inputs and its approver.
We have a stated position on where data may be processed and by whom.

Execution path

A recommendation that a human must retype into another system is not automation.

Our core systems can be written to through an API or an integration layer, not only through their screens.
There is an approval step an automated action could be routed through.
An action taken in error could be identified and reversed.
Reading the Result

What the score actually tells you.

A low score is not a verdict. It usually means one dimension is holding the others back, and that is a smaller problem than it looks.

0–39

Reporting

The organisation can describe what happened. Decisions are made from exports and experience. Start by writing down one recurring decision and the inputs it really uses — not the ones it is supposed to use.

40–59

Analysing

Prediction exists somewhere, usually in one team. The gap is the handover: the forecast is produced, then a person carries it to the system where the action happens.

60–79

Recommending

Recommendations reach the people who act on them, with reasoning attached. The remaining work is usually governance: agreeing which actions may proceed without a signature.

80–100

Acting

Agents can be given real scope: bounded decisions they execute, logged and reversible, with people supervising the exceptions rather than the routine.

Go Deeper

Get the written breakdown.

The score tells you roughly where you stand. The breakdown tells you which single change moves it most, based on what we see in organisations that answered the way you did.

  • Your four dimension scores, with the two questions dragging each one down.
  • The decision we would automate first in an organisation shaped like yours.
  • What would have to be true before that decision could run without a person.

    Veraius agents

    What your teams gain from Veraius agents.

    Finance

    Budget against reality

    Planned and actual spend are compared by cost centre, and variances above your threshold are escalated with their cause.

    See the Finance agents
    Manufacturing

    Capacity against orders

    Open orders are compared with available capacity so delivery risk shows before a due date is missed.

    See the Manufacturing agents
    IT Operations

    Changes approved by risk

    Low-risk changes move fast; high-risk ones go to the change board with the evidence already gathered.

    See the IT Operations agents

    In every department

    • Agents prepare the work on your own data; your people approve what happens next
    • Plain-language questions answered from live ERP data, with tables and interactive charts
    • Grounding check: numbers that cannot be traced to a source are not shown
    • Explainability, confidence and risk scores with decision rationale
    • Slack, Teams, WhatsApp and Signal channels with an approval inbox
    • Department-based access policy with personal data masking

    All agent departments

    Questions

    Frequently asked questions

    Straight answers about integrations, deployment, security and cost — including where the honest answer is "it depends".

    Ask your own question
    What does the readiness assessment measure?

    Four dimensions: whether the data behind your decisions is reachable, whether the decisions themselves are defined and owned, whether governance can accept a system acting, and whether the operation can absorb a recommendation inside its decision window. An AI agent readiness assessment that only scores data maturity misses the three that actually stall projects.

    How long does the readiness assessment take?

    Around fifteen minutes, and it produces a score with the specific gaps named rather than a grade. The useful output is the shortest list of things to fix first, since readiness is rarely uniform — most organisations are strong on data and weak on decision ownership.

    What if we get a low score?

    That is the more useful result. A low score on decision ownership tells you the next step is a conversation inside your organisation rather than a software purchase, and knowing that before a deployment is worth considerably more than knowing it during one.

    Request a Demo