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Service 08 · Artificial intelligence

They suggest, act and report back.

Copilots beside your team and agents that carry out tasks in your systems: they look up, enter and check. With a person at the decision point.

Talk to Kadelta How it works

What we measure

Accuracy on evaluation cases
Target 95% to go live
Tasks done without a person
Target by task type
Hours of manual work per week
Target set in the proposal
Cost per task
Target in the panel

The before

It makes sense when

  1. A process has exceptions only one person can handle

    Signups, quotes and checks stop when that person is out.

  2. Repeat work eats the day

    Copying, checking and entering by hand, every day, the same way.

  3. The AI stayed a pilot

    The test impressed in the meeting and never reached the operation.

The after

What Kadelta delivers.

  1. One flow, one metric and one owner for each agent
  2. Copilots inside the system your team already uses
  3. Agents that look up, enter and check in your systems
  4. A person approves where there is risk
  5. A log of every action the agent takes
  6. Cost per task measured

Copilots

They work next to your team, inside your system: summarize history, draft the proposal, suggest the reply. The decision stays with the user.

Autonomous agents

They get a goal and carry out the task in your systems: look up, enter and check. With clear limits on what they do alone and a log of every action.

Capabilities

Agents in operations.

  1. Repetitive work eats the day

    Agents that do the work

    What it is
    Agents that access systems and complete tasks, under defined rules.
    Where it fits
    Data entry, checks, quotes and postings in the systems the team uses.
    How it is delivered
    Limits on what they do alone, approval where there is risk and a log of every action.
    What we measure
    Tasks completed without a person and cost per task.

  2. Many channels, their own rules

    Omnichannel and complex flows

    What it is
    Several channels, integrations and business rules in a single flow.
    Where it fits
    Operations running WhatsApp, website, email and internal systems at once.
    How it is delivered
    Flow design, integrations and rules by proposal, with test cases before launch.
    What we measure
    Accuracy per flow step and end-to-end time.

Scope, usage and third-party integrations go into the proposal.

How it works

Four steps, measured.

  1. Step 01

    We pick one flow

    One process, one number that matters and one person responsible for it.

  2. Step 02

    Real cases before code

    Without cases that have the right answer, the agent does not start.

  3. Step 03

    Limits and approval

    The agent prepares and suggests. Where there is risk, a person approves, and every action is logged.

  4. Step 04

    Tested on every change

    New model or new instructions? The cases run again before release.

Questions

Frequent questions.

Does the AI decide on its own?

Only within the agreed limits. Where there is risk, a person approves.

Do we need to switch systems?

No. The agent works in the systems the company already uses.

How do I know it is working?

Each agent has a metric, an owner and its cost per task measured, and the evaluation cases run on every change.

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What's your before?

A 30-minute conversation to measure where you are today.

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