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Seventy-three percent of your shrink is preventable, and most of it is not theft.

Inventory error and process failure quietly cost more than the losses you investigate.

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1.6%

of retail sales lost to shrink, against a total US figure of roughly $90 billion.

Source: NRF National Retail Security Survey

What is happening

Most of your shrink is preventable, and the till already knows where.

73% Of shrink is preventable

Employee theft accounts for 29% at around $26 billion. The rest is inventory error and operational inefficiency — the part nobody investigates.

Stock accuracy decays between counts

The system says one thing, the shelf says another, and the gap is discovered at the point where it costs a sale.

Channels disagree about the same item

Store, warehouse and online each hold a version of availability. Overselling and cancelled orders follow.

Margin by SKU is a month-end discovery

Discounting, returns and shrink are known individually and combined too late to change a buying decision.

Intelligence, plumbed in

A supplier catalogue in any format becomes one product record.

The unglamorous half: a connector per supplier, one product meaning in the layer, and a scored test set of real lines.

How we make AI survive real data
  • Connectors
  • A semantic layer
  • Evals you can check

What changes

Judge us on this, not on what we built.

Found

Shrink attributed to cause, not just measured

Separating theft from receiving error, transfer error and system error — because each has a different fix.

Accurate

One stock position across every channel

Reconciled between POS, warehouse and online, so availability is true at the moment of sale.

Sooner

Margin visible while you can still act on it

By SKU, store and channel, net of discount, return and shrink.

Research

We wrote a full page on each of these, with the sources.

Each one carries its own figures and the citations behind them. Start with whichever sounds most like your week.

However hard, whatever it is

Shrink is one example. Bring the number nobody can explain.

We wrote this about stock the system cannot see. If yours is returns, ranging or a supplier catalogue in nine formats, same approach.

  1. 01

    We sit with you

    Days where the work happens, not a workshop in a meeting room. We watch the job get done and write down the shortcuts nobody wrote down.

  2. 02

    We read everything

    Your data, your rules, your vendors and their documentation, and the published research on your sector. We report what is actually in there.

  3. 03

    We break it to first principles

    Not which tool fixes this. What is actually causing it, taken apart until we reach the piece that cannot be divided further.

  4. 04

    Then we build

    Weeks, not quarters. By this point we are not guessing what to build, and guessing is the thing that makes projects long.

Where we sit

Your store platform stays. We build what your stock cannot see today.

4

What you get

  • Found Shrink attributed to cause, not just measured
  • Accurate One stock position across every channel
  • Sooner Margin visible while you can still act on it
3

Built new for you — none of this exists in your stack today

  • A shelf sensor for stock the system cannot count
  • A store tablet that makes a count take ten minutes
  • A shrink board that names the aisle and the hour
2
The stock-truth layer Reads your tills and warehouse. Moves no stock on its own. Connectors, one agreed meaning per field, and a model reading what no field holds. Accuracy measured on your own records.
1
  • Shopify
  • WooCommerce
  • SAP Retail
  • NetSuite
  • POS systems

What you already run — unchanged, and still yours

If the store touched it, we can read it. A till with a nightly file, a warehouse system with no API, a shelf nothing is counting. All of it is reachable.

  • No API
  • No documentation
  • A terminal from 1994
  • It arrives as paper
  • The vendor said no
  • It reports nothing

Not a list of limits. Name yours on the call.

And once we can reach it, a model can read it. Most of the value here is in the sources nobody ever structured — the note, the letter, the screen.

Who this is for

The people who feel this first

  • Head of Retail Operations
  • Supply Chain Manager
  • Loss Prevention Lead
  • E-commerce Head
  • CFO

Straight answers

The questions you would ask on the call

  • Is this loss prevention software?

    Partly, but the larger opportunity is not theft. About 73% of shrink can be prevented. Most of it is stock and process error, not theft. That makes it a data problem, not a security one.

  • We run stores and online on different systems. Is that a problem?

    It is the normal situation and it is the actual work. Reconciling them into one truthful stock position is usually the single highest-value thing we do for a retailer.

  • Do we need to replace our POS?

    No. We read from it. Replacing a POS is disruptive, expensive and rarely the cause of the problem.

  • Can AI clean up supplier catalogues?

    Any format becomes one product record. We score the mapping against real lines, and report which suppliers still need a human eye.

Next step

Start with your own numbers.

  1. We talk

    20 minutes. Free.

    You tell us what is not working. We ask how the work really gets done.

  2. We look at your data

    A few weeks.

    We read your systems, including the notes and letters no field holds. You get what is really in there, what it costs, and the accuracy we can hit.

  3. We build

    A few months.

    Only if step 2 says it is worth it. Fixed price, agreed before we start.