Our rules

How we keep your numbers true — written down, not improvised.

The rules we work by, the daily rhythm, who may do what, and how the system is built. The same for every client.

Five rules that came from running a real operation.

We didn't start with a theory. Most of these began as real errors.

  1. 1

    Block what can't be right; warn on what might be.

    Structural errors are refused. Judgement calls are blocked only when two signals agree — a single odd value just gets a warning.

  2. 2

    Close the day the next morning, not at midnight.

    Late entries are normal. Books close after the night shift, then are reconciled and re-checked before 8 a.m.

  3. 3

    Never delete and re-run a closed day.

    That counts everything twice. A closed day is undone, re-closed, and the difference carried forward.

  4. 4

    Date real changes; let corrections reach back.

    A new price applies from its date. A fixed mistake applies to the past too, so it never returns in old reports.

  5. 5

    Rehearse every correction.

    Backup → test copy → verify → apply, with a named approver. A guard refuses anything unrehearsed.

Every morning

The same rhythm, every day, for every client.

The owner's work changes from assembling and tracing numbers to deciding the few that need judgement.

  1. 06:00

    The day closes

    Yesterday is closed after the shift; reconciliation and checks run.

  2. 07:00

    Exceptions triaged

    Explained, fixed by procedure, or raised with your operations lead.

  3. 08:00

    Morning report

    Summary to the owner and ops team: yesterday's numbers and what needs a decision.

  4. Daytime

    Watch

    Missing forms, negative stock and data edits are monitored all day.

  • WeeklyLate-entry scan → re-close changed days → weekly cost report with drill-down
  • WeeklyPrice review queue cleared with you
  • MonthlyCost & purchase-planning reports; thresholds and rules reviewed with the owner
  • MonthlyUser review: leavers switched off, new staff trained

Controls

Who does what — written down, not assumed.

AI does the routine. But nothing touches live data without a recorded “go” from a named person.

01
Detect

A trigger: an incoming message, a schedule, or a number that's off.

  1. 01
    Detect

    A trigger: an incoming message, a schedule, or a number that's off.

  2. 02
    Suggest

    AI prepares a proposed action, with its reasoning.

  3. 03
    Approve

    Approved at the level you set for that action.

  4. 04
    Act

    Carried out in your systems, and logged.

  5. 05
    Measure

    How often suggestions are accepted, plus one outcome number.

The system
Does on its ownRecords every step, applies the rules, morning & daytime checks, alerts, scheduled reports
Cannot doBook an entry a guard refuses: wrong unit, unmapped item, back-dating, unbalanced book
The AI agent
operating layer
Does on its ownReads the record, investigates anomalies, prepares reports, rehearses corrections on the test copy, drafts improvements
Needs a recorded “go”Any change to live data, any software release, any unscheduled message to your team
Cannot doApply a live correction not rehearsed within the last hour
Our approver
Needs a recorded “go”Signs off every live change and every release
You
owner / operations lead
Does on its ownSet the business rules, review price moves outside the band
Needs a recorded “go”Co-sign corrections that change numbers already reported to you

You decide how far AI is allowed to act.

Approval is set per action. Start strict, and raise it only once suggestions prove accurate.

L0L1L2L3L4

Slide to set how far AI is allowed to act

L2Prepare
AI

Prepares a draft.

Your team

Approves before it runs.

Drafting an order from a WhatsApp message.

How far you want to be consulted is agreed at the start. Silence is not approval.

Every correction takes the same path

  1. 1Backup
  2. 2Dry run on test copy
  3. 3Apply on test copy
  4. 4Verify before–after
  5. 5Live dry run
  6. 6Approved
  7. 7Applied & logged

A guard refuses the live apply unless the same correction was rehearsed on the test copy within the last hour.

How we choose the fix

AI is the last step on the ladder, not the first.

Every Petakan finding gets an Opportunity Score, then climbs from the bottom rung. We stop at the lowest rung that actually solves the problem.

Opportunity Score
FrequencyTime per occurrenceCost of errorsRule clarityData availabilityRisk

Many problems are solved on rungs 1–4. That's good news: cheaper, faster, easier to maintain.

  1. 1Remove

    Does this step need to exist?

    A duplicate report nobody reads.

  2. 2Simplify

    Can hand-offs and approvals be reduced?

    Three signatures for a small purchase.

  3. 3Standardise

    Are the format and rules clear?

    One order template for every channel.

  4. 4Automate

    Rules are fixed? Let a machine run them.

    Daily sales recap from every marketplace.

  5. 5AI

    Needs judgement? Only then use AI — with approval.

    Reading free-text order messages into a draft order.

How we work with you

PRIMA, phase by phase

What happens in each phase, what you hold at the end, and when it counts as done.

  1. P

    Petakan

    Map2 weeks · fixed price
    What happens

    Our team walks your workflow end to end, on site, with the people who do the work — every place stock or work sits, every hand-over, every way value is lost.

    What you keep

    One-page process map, list of loss points, improvement recommendations, estimated hours and cost to save.

    Done when: The workflow fits on one page and you agree with it.

    No big contract lock-in

    After Petakan, the process map and recommendations are yours — continue or stop there. Target: first process live in 8–10 weeks.

  2. R

    Rancang

    Design1 week
    What happens

    Map the workflow onto the same template we use for every client. Agree treatment rules, the reports you need, the baseline and the approval level.

    What you keep

    Model document, list of forms & reports, business case — signed off by your process owner.

    Done when: Every movement on the map has an event type, a rule and a written approval level.

  3. I

    Implementasi

    Implement4–6 weeks
    What happens

    Set you up as your own tenant, load master data with scripts that check before writing, and prepare the forms — on top of the systems you already use.

    What you keep

    System ready, forms tested, master data you have reviewed.

    Done when: You have reviewed the master data and every form passes on the test copy.

  4. M

    Mantapkan

    Embed2–4 weeks
    What happens

    Train the team in their language, run in parallel with the old way, switch on the morning checks. The first count sets the opening balances.

    What you keep

    Live system, a team that actually uses it, the first weekly report.

    Done when: Two clean closes in a row, and the first weekly report matches your own numbers.

  5. A

    Amati

    MeasureOngoing
    What happens

    Every morning yesterday is closed, checked and reported. Exceptions are fixed by procedure, then turned into new rules.

    What you keep

    Daily, weekly and monthly reports — and a system that gets safer every month.

    Done when: Ongoing — then add sites, flows and reports.

Under the hood

ERPs model documents. We model the work.

For your technology team: why the data structure is different, and why it's possible now.

Show technical detail ↓

Typical transaction systems

  • ○Mutable document tables (stock = one number overwritten)
  • ○Validate format, not plausibility
  • ○Close once a month
  • ○Corrections = overwrite or manual adjusting journal
  • ○Rules live in configuration and consultants' heads

Our platform

  • ●One identity per item in one base unit; packs & supplier codes mapped per site
  • ●Every movement = a document + a double-entry journal row pointing to its source
  • ●Daily balance per location: closing = opening + in − out ± adjustment
  • ●Guards compare each entry with that item's own history
  • ●Corrections are scripts — rehearsed, approved, carried forward
Sources→Events→Ledger→Daily close→Views

Why now

AI agents that use tools and write code

Investigating anomalies and writing corrections used to need an analyst per client. Now an agent does the routine — making a daily close economical for mid-market businesses.

Guardrails for agents near production

Tool boundaries, scoped permissions, approval gates and full logs let an agent work on real books without blind trust.

Ledger architecture at commodity cost

Reconciling every day per location is now cheap — not just at month-end.

Capture at the edge

Every staff member has a phone. Forms in their language put recording where the work happens.

From true numbers to decisions

Analysis is only as good as the data beneath it.

We don't bolt dashboards onto dirty data. We make the operational data true first.

Live
  • ✓Drill-down from any cost total to the supplier lines, recipes and people behind it
  • ✓Cost % per view: came in · used · served
  • ✓Loss & yield against each item's baseline
  • ✓Recipe-cost drift alerts & price review queue
Next
  • →Variance decomposition: price · usage · yield · mix · volume
  • →“What if” sensitivity analysis
  • →Demand forecasting
  • →Posting straight to the accounting system

FAQ

More questions

What about our data?+

Your data stays yours. Each playbook reads only what it needs, every action is logged, and memory is visible and deletable by you.

What if it isn't a fit?+

Every phase has a decision point. After Petakan, the process map and recommendations are yours — you can stop there.

Does this replace our staff?+

The aim is to give the team's time back from repetitive work to work that needs judgement. People stay in charge.

Start with one process.

Two weeks, fixed price. The process map and recommendations are yours.

Map one process →