F7 KORE
Traceability · Trace

Know where each record came from and how much each process gained.

Map processes, compare before and after with AI, calculate the savings and anchor each dossier in a tamper-evident trail that independent auditors can check.

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Trace
Lineage

The origin and destination of every record.

Links are created in day-to-day work, between records, documents and tasks. Each one states the relationship, who linked it and when. What wasn't found is shown, with no simulated complete chain.

Record lookup

Origin, journey and decision memory.

  1. 01

    Lineage

    The record's origin and destination, across levels, with the relationship, who linked it and when.

  2. 02

    Journey

    Where the item has been, with whom, when and the time since the previous step.

  3. 03

    Decision

    The meeting, the decision made, the document that recorded it and its versions.

  4. 04

    Sources consulted

    The documents the agent read to answer about the item, with their version. The question and the excerpt are visible only to the person who asked.

Dossier

Exportable dossier with integrity verification.

Export lineage, journey, decision and agent queries as PDF and spreadsheet, with a SHA-256 digest recorded in the audit trail. With the spreadsheet, recalculate that digest without access to the system, and any change produces a different value. The dossier contains what the person who generated it can see.

Process mapping

From interview to approved baseline.

The AI agent interviews the people who perform each activity, through Teams or email; in the app, each person fills in their own form. What was stated is compared with what is recorded and between people, and someone decides which number stands. The map can also come from a spreadsheet, diagram, consulting report or on-screen entry, with each number linked to its origin.

  1. 01

    Scope

    Process, areas, participants, channel, deadline, message and script

  2. 02

    Interviews

    Each person's answers, in a saved conversation or a completed form

  3. 03

    Reality check

    Stated compared with recorded, and between people

  4. 04

    Consolidated map

    Activities with the origin of each number

  5. 05

    Suggested proposal

    Suggested outcome for each activity, open to editing and approval

  6. 06

    Report and approval

    Once approved, the map becomes the baseline

Baseline

Hours, cost and people for each activity.

The baseline records effort, duration, frequency and role, with the origin of each number. Once the proposal is approved, it changes only through a new import or a new mapping, in a new version, with a record of who saved it. Salary-derived values appear only to those with permission.

Before and after with AI

Estimated gain compared with actual.

The AI agent suggests what happens to each activity: it stays with the person, the person does it with the agent, the agent does it, or the activity is dropped. The approved proposal can't be edited: each change creates a new version. Compare the estimated gain with the gain measured on cases completed under the new model.

Before vs. after · cost per month

Before$32,600

1,530 person-hours

With AI, projected$16,500

684 person-hours

With AI, actual$17,100

863.8 person-hours

Value of hours freed up, projected
$16,100/month
846 h/month · $193,200/year
Value of hours freed up, actual
$15,500/month
666.2 h/month · $186,000/year

Person-hours returned to the team, valued at the hourly cost of each role, with no reduction in payroll implied. The value depends on the hourly cost of each role, so hours and dollars don't fall in the same proportion. Demonstration values.

Impact report

The gain over 1, 5 and 10 years, with measured and projected kept separate.

Year 1 starts from the measured figure, when the process already runs under the new model, or from the figure projected by the approved proposal. From year 2, the conservative scenario considers salary adjustments and gain erosion; the expected scenario adds volume growth; the optimistic scenario adds new processes. Each assumption states whether it was measured or provided by the company. Hours freed up, acceleration and avoided loss are shown separately, with no total.

Estimated vs. actual

Estimated
Actual
  • Hours freed up

    People's time returned for other work

  • Acceleration

    Reduction in the calendar time of the case

  • Avoided loss

    Estimated loss avoided, with the assumption stated

The three gains are shown separately, never added together, with the AI cost alongside.

The process on the work board, with the role of each step.

Traceable decisions and actions, from the source of each number to the person who owns the fix.

Talk to our team and see what F7 KORE can do for your operation.

Product screens and values use demonstration data.