Use case · restaurants & retail

The daily close where every fee ties back to the deposit

The agent reads the files your operation already exports — POS reports, processor deposits, supplier invoices — and writes a close where every sale, fee and deposit points to its source line. Each manager sees only their own location.

The question this use case answers

How does a US multi-location operator reconcile POS sales with processor deposits and compare margin per location with every figure traceable to its source report?

The files you already have

  • POS end-of-day reports (.xlsx / CSV)
  • Card-processor deposit statements
  • Supplier invoices (PDF / CSV)
  • Bank deposit files (CSV / OFX)
sample

What was the effective processor fee in May?

2.7%

deposit_may_locationA.csv · D2:D310 · you have access

Illustrative figure (sample) with fictional data — not a customer result or benchmark.

How the agent handles it, step by step

  1. 1

    Upload the day's or month's close

    Drop in the POS reports and processor deposits. No integration — the agent identifies each format on its own.

  2. 2

    The agent reconciles sale, fee and deposit

    Every figure carries where it came from: file, tab and line. The effective-rate and margin math is deterministic — the AI writes the prose, never the number.

  3. 3

    A deposit with no statement becomes a gap

    If a processor statement hasn't landed, the agent flags the gap instead of closing the drawer over a hole.

  4. 4

    Schedule the per-location close

    Save the recipe and the agent re-runs it each period, comparing locations with the same versioned audit trail.

Permission at synthesis time

Across a group, each manager answers for their own location — and should not see the neighboring one's result. Redijo checks the permission of each fragment at synthesis time: a manager sees their own location's margin, and another store's figure never enters the answer, not even inside a group total they cannot open.

In restaurants and retail, margin lives in the details: the processor fee that crept up, the deposit that came in light, the purchase booked at a different price. The trouble is those figures are scattered across POS reports, processor statements and invoices — and nobody can trace the result back to the source line. Generic AI confidently summarizes it and hides exactly where the money leaked.

Redijo starts with the proof. The agent reads the files your operation already exports and writes a close where every sale, fee and deposit points to its source line.

Auditable by construction

The proof is born with the answer. Before writing a figure, the agent locates it in a file you uploaded and records its origin — file, tab, line. The effective-rate and margin math is deterministic; the AI writes the prose around it, never the number. That is why the close is auditable, not just plausible.

Each manager sees only their own location

The second win shows up when you compare locations. Almost every tool checks access only at retrieval — then lets the AI blend everything into one answer. Redijo checks the permission of each fragment at synthesis time: a manager sees their own location’s margin, and another store’s figure never enters the answer, not even hidden inside a group total.

Who it’s for

For the group owner comparing locations, the manager closing the day’s drawer, and the controller who needs every fee traced back to the statement. Your data is hosted in the cloud, with international-transfer safeguards.

Questions this page answers

Each location's data is hosted in the cloud, with international-transfer safeguards — a residency posture you can put in writing, never a marketing line.

Close the drawer with figures you can audit

Get started and reconcile POS and processors from the files your operation already exports.

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