Amazon FinOps Provider
Automated recovery for Amazon vendors. Bots that audit lost revenue across millions of data points, find what the marketplace owes and get it recouped, without anyone reconciling a spreadsheet.
Overview
Selling to Amazon at scale means losing money in ways that are hard to see. Shortages, chargebacks and pricing errors accumulate across hundreds of thousands of transactions, and finding them means reconciling data nobody has time to reconcile.
Our client audits those losses for Amazon vendors and recoups the funds, on a platform that runs on logic rather than on people.
Their platform conducts audits of lost revenue and processes very large volumes of data points to recover money owed back to the vendor, with no manual interference in the accounting itself.
They came to Sphinx Solutions wanting the remaining redundant tasks automated and more transparency in the process, with their global services organised on a single platform.
We automated the process end to end. Their own aim is fair and transparent accounting for worldwide eCommerce, and the automation is what makes that claim keepable at volume.
eCommerce vendors hit reconciliation problems on everything from allocating man-hours to shipping logistics, and the financial and human resource it takes to chase them gets stretched dangerously thin.
A platform that processes accounting data with no manual interference is dynamic by design, and that is exactly what makes it daunting to automate.
The client already offered logic-based, AI and ML-driven recovery. What they needed was the surrounding process automated to the same standard, so the platform was consistent end to end rather than automated in the middle and manual at the edges.
We ran an in-depth analysis of the requirements before choosing anything, then matched the tools, technologies and approach to what the process actually does.
The measures that mattered were business process coverage, efficiency, accuracy and return, in that order. In recovery work an inaccurate bot is worse than no bot, because it files claims that are wrong.
We delivered end-to-end RPA covering the accounting automation and the business processes around it, built on UiPath.
Automation in this domain is judged on accuracy rather than speed, and that is what the build was optimised for.
“Sphinx Solutions offered very competitive and effective RPA solutions. Their functionally rich and advanced development helped us automate our entire process. Our vision is to empower transparent and fair accounting for worldwide eCommerce, and their team of experienced developers helped us complete the project in a friendly and professional manner. We are extremely lucky to have found Sphinx as our technology partner.”
Tech stack
What people usually ask about Amazon FinOps Provider and about building something like it.
Financial operations on the marketplace itself: reconciling what Amazon owes against what it has paid. Shortages, chargebacks, pricing and returns discrepancies all cost a vendor money quietly, and finding them means auditing transaction data at a volume nobody can work through by hand. It is a different discipline from cloud FinOps, which manages AWS and Azure spend and happens to share the name.
Because the work is high volume, rule-based and only worth doing if it is done completely. A human sampling the data finds some of the money; a bot working through all of it finds the rest, and does it again next month without being asked.
Accuracy above everything. A recovery claim built on a bad reading is worse than a claim never filed, so the document capture, extraction and recognition have to be right before speed matters at all. That is why the consultancy and testing stages carry more weight in this kind of project than the bot building does.
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