Find the money leaking between your store, payouts, carriers, and 3PL.
We start with operational recovery: 3PL discrepancies, carrier claims, payout exceptions, and chargeback evidence. The output is measurable money recovered and manual review removed, not a vague productivity promise.
Start with one recovery workflow.
A narrow first build compares what should have happened with what was billed, paid, shipped, or disputed. Clear matches pass automatically. Exceptions reach a human with the evidence attached.
See the demo-tested scenario →Signals we look for
- A 3PL invoice is approved without line-by-line reconciliation
- Carrier claims or service credits are handled only when someone remembers
- Payout, order, refund, and fulfillment records are reconciled in a spreadsheet
- Chargeback evidence is assembled manually across several systems
What the build produces
- An exception queue with a reason and next action
- A recovery ledger that counts only credited money
- Human approval for disputes, claims, and ambiguous matches
- A low, base, and high savings model built from your volumes
When we are not the right choice: Not a fit when a configured feature in your current stack already handles the workflow well, the volume is too low to measure, or the process changes every week.
What we automate here
The daily, costly, repeatable work, not a sprawling platform.
Operations
- Order & data reconciliation across tools
- Copy-paste between systems that don’t talk
- Status updates and handoffs chased by hand
Finance
- Invoice matching and chasing
- Expense and receipt sorting
- Month-end numbers rebuilt manually
Fulfillment
- Shipment and tracking exceptions
- Returns triage and routing
- Inventory sync across channels
Support
- Repetitive ticket triage and tagging
- “Where is my order?” auto-answers
- Draft replies from your knowledge base
A build like yours
Labeled honestly: representative until a client signs off.
The questions people ask first.
This sounds too good to be true. What’s the catch?
Three honest ones. First, we only take on processes where we’re confident in the projection, so we say no a lot; if a process is too messy or too small to measure cleanly, we won’t pitch it. Second, the shortfall refund requires that the system was actually used as set out in the agreed scope, so we’re measuring the automation and not a process that quietly went back to the old way. Third, we’re a young firm still building a public track record, which is exactly why the risk sits with us and not you: the guarantee stands in for the years of case studies we don’t have yet. You can check who we are on our about page and register entry, and on LinkedIn.
How do you define and measure “savings”?
Before we build, we agree a baseline together: the labor hours your team spends on the process times their loaded cost, plus any tool licenses we’ll replace and the cost of errors and rework. From that we set a projected Year-1 saving and write it into the scope. After launch we re-measure the same line items, so the number is transparent and mutual the whole way through.
What if the savings come in smaller than expected?
Then we correct the fee. If projected savings were $40,000, the delivery fee would be $20,000. If verified savings later came to $30,000, the corrected fee would be $15,000 and we would refund $5,000. The system has to have been used as set out in the agreed scope, so we are measuring the automation rather than a process that quietly returned to the old way.
How fast can you build something?
Most first automations are working in 5 to 10 days, not months. We deliberately scope the first build narrow, around one painful, costly process, so you see real output quickly. Speed is part of the model: the sooner it runs, the sooner the savings start.
See what a Savings Audit would find in your dtc / ecommerce business.
20-minute fit check · no obligation · measured audit for qualified processes.