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Case study · Logistics and last mile

Logistics operator: replacing a two-decade-old system with an agentic ERP that balances to the cent

KINTO replaced a two-decade-old system and a macro-driven spreadsheet with an agentic ERP that matched the old system to the cent on 100% of shared waybills over six months and surfaced customer-reactivation opportunities.

By KINTO · Published

Figures, each with its source

  • hundreds of thousands (more than a decade)

    historical waybills loaded

    Measured

  • 100% of shared waybills, 6 months

    reconciliation against the old system

    Measured

  • ≈29–50% depending on tonnage

    freight savings from the semi-bulk load rule

    Measured

Ranges or orders of magnitude where a figure could identify the client, each with its source.

How the transformation unfolded From the problem to what changed, in the five steps every KINTO case follows.
  1. Problem

    The operation ran on a web application more than twenty years old, with obsolete dependencies and hundreds of thousands of waybills in one database.

  2. Signals

    Four signals: market, business, user experience and support.

  3. How we understood it

    We audited the legacy system, turned recorded meetings into a prioritized list with code-level verification, documented that platform’s real limits, and validated waybill by waybill (not by totals) across six months of billing periods.

  4. What we built

    A rescue of the old system without rewriting it, an agentic ERP with automatic ingestion, full history and a financial engine, a labeling tool for sticker printers, and a public site with an SEO/GEO layer.

  5. Transformation

    Six months of billing periods matched the old system to the cent on 100% of shared waybills, with the remaining differences explained one by one, and the ERP surfaced customer-reactivation opportunities: high-value customers who had stopped shipping.

Before and after, by dimension Editorial levels from 0 to 4 read from the text of this case, never a figure drawn to scale.
  • Core system

    Before

    Two-decade-old app (level 1 of 4)

    After

    Agentic ERP (level 4 of 4)

  • Financial close

    Before

    Macro-driven spreadsheet (level 1 of 4)

    After

    Financial engine in the ERP (level 4 of 4)

  • Customer accounts

    Before

    Not visible in time (level 1 of 4)

    After

    Reconciled per customer (level 4 of 4)

  • Customers going quiet

    Before

    Went unnoticed (level 0 of 4)

    After

    Reactivation surfaced (level 3 of 4)

The four signals we read What the market, the business, the user experience and support were saying before KINTO built anything.
  • Market

    The company works on the platform of a third party that settles its earnings, so keeping each waybill’s accounts right per customer is the business.

  • Business

    Each customer’s activity was not visible in time: customers who stopped shipping went unnoticed.

  • User experience

    Dozens of screens per task and real operational errors (files downloading with broken names).

  • Support

    Receipts and waybill statements are sent over WhatsApp and email.

From legacy audit to human by exception
  1. Legacy audit Tables and volumes
  2. Meetings to list Prioritized, verified in code
  3. Waybill by waybill Not by totals
  4. Human by exception Autonomous by default

Connections

  • Legacy audit → Meetings to list
  • Meetings to list → Waybill by waybill
  • Waybill by waybill → Human by exception

KINTO replaced a two-decade-old system and a macro-driven spreadsheet with an agentic ERP that matched the old system to the cent on 100% of shared waybills over six months and surfaced customer-reactivation opportunities.

Problem

The operation ran on a web application more than twenty years old, with obsolete dependencies and hundreds of thousands of waybills in one database. The twice-monthly financial close lived in a macro-driven spreadsheet, and every day someone retyped data that already existed on a third party’s platform.

Signals

  • Market: The company works on the platform of a third party that settles its earnings, so keeping each waybill’s accounts right per customer is the business.
  • Business: Each customer’s activity was not visible in time: customers who stopped shipping went unnoticed.
  • User experience: Dozens of screens per task and real operational errors (files downloading with broken names).
  • Support: Receipts and waybill statements are sent over WhatsApp and email.

How we understood it

  • Legacy system audit: inventory of tables and volumes.
  • Recorded, transcribed meetings (one of nearly four hours) turned into a prioritized list, each item with its timestamp and a verification in code.
  • Authorized analysis of the third party’s platform: its real limits were documented.
  • Waybill-by-waybill cross-validation, by waybill number rather than totals, across six months of billing periods, plus an economic valuation of the ERP with every figure labeled measured, market or estimated.

What we built and why

  • Rescue without a rewrite: the old system was stabilized and redeployed, bulk loading was rewritten (from timeouts to a fixed number of queries per batch), and automated tests were added.
  • Agentic ERP replacing the application and the spreadsheet: automatic ingestion from that platform several times a day, full history loaded behind verification gates, a single customer master, a financial engine (daily consolidation, settlement with configurable taxes, billing statements, receivables, treasury) and a compatible facade so a large customer’s integration kept working.
  • Labeling tool for sticker printers: a waybill of N boxes produces N labels with a valid barcode in one click, licensable per customer, with no content leaving the browser.
  • Public site with an SEO/GEO layer, structured data and conversion tracking.

Why this way: The guiding principle was “autonomous by default, human by exception”: the new system handles the routine on its own and calls a person only when something falls outside what is expected.

Transformation

  • Six months of billing periods matched the old system to the cent on 100% of shared waybills; the remaining differences were explained one by one. Receivables reconciled customer by customer.

  • New visibility: customer-reactivation opportunities among high-value “dormant” customers, detected by the system.

  • Active production with the old system frozen.

  • historical waybills loaded: hundreds of thousands (more than a decade) (measured)

  • reconciliation against the old system: 100% of shared waybills, 6 months (measured)

  • freight savings from the semi-bulk load rule: ≈29–50% depending on tonnage (measured)

What we don’t know yet

  • Data-entry hours saved: the valuation itself calls for timing them.
  • A pay-for-results pricing model was analyzed, with no agreement closed to date.
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