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handeliv

Method

How we separate the work.

Before any tool is installed, the work is mapped — then it is decided which steps still need human attention, and which do not.

The system

One connected system, not four separate projects

Handeliv provides an integrated system for AI work transformation. The four layers depend on each other — when one layer operates alone, an AI initiative is less likely to create lasting change.
SYSTEM LAYERS

  1. Workflow

    Mapped, redesigned, then agreed.

  2. AI capabilities

    Applied to defined steps.

  3. People

    Equipped to run and review the new way of working.

  4. Measurement

    A baseline agreed before anything changes.

An illustration of the method, not a product interface.

We decide which steps no longer need human attention — so that people can do the ones that do.

AI capabilities

AI runs the parts of the work that have been defined

AI can support or carry out parts of a workflow whose boundaries have been agreed. The person accountable still reviews the result before it moves forward.
AI AGENT — EXECUTION TRACE
  1. Incoming request

    A request arrives by email, ticket, or system record.

  2. Understand context

    The agent reads the context and matches it against relevant patterns.

  3. Retrieve information

    The agent pulls the relevant data from its defined sources.

  4. Prepare action

    The agent drafts the action or the response, without sending it.

  5. Human review

    The person responsible reviews the result before the action or response goes out.

  6. Response sent

    The response is sent, the result is recorded, and the workflow continues.

An illustration of the method, not a product interface.
THE BOUNDARIES WE WRITE DOWN
—
Scope

What the agent may do, and what falls outside its boundary.

—
Data access

Which sources it may read, and which it may not.

—
Actions

What it may do without approval, and what it may not.

—
Trail

What is recorded so it can be reviewed later.

An illustration of the method, not a product interface.

Measurement

A value model, not a promised outcome

The chain that has to hold before any number means anything. The baseline is set before anything changes, then re-measured in exactly the same way.
VALUE MODEL

  1. STARTING POINT

    Baseline

  2. DESIGN

    Redesigned workflow

  3. DEPLOYMENT

    AI-supported steps

  4. CONTROL

    Human review before results move forward

  5. USE

    Adoption

  6. RECORD

    Operating evidence

  7. VALUE

    Business value where applicable

Illustrative framework. Actual outcomes depend on the workflow, implementation context, adoption, and agreed measurement baseline.
MEASUREMENT DIMENSIONS
—
Workflow volume

How many cases run in a given period.

—
Cycle time

How long a case takes from start to finish.

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Repetitive effort

Manual steps performed over and over.

—
Workflow completion

How far a workflow runs before it is finished.

Illustrative framework. Actual outcomes depend on the workflow, implementation context, adoption, and agreed measurement baseline.

We show no numbers until the numbers are yours. The value for each dimension comes from your own baseline, not from an example.

Start with one workflow.

A diagnostic session determines which steps still need a person — and if the answer is “all of them”, we will say so.

Book a diagnostic call