One percent of what you buy is billed wrong, and nobody reads the invoice that says so.
On $100 million of vendor spend that is $1 million a year. Recovery audits on spend nobody has checked before find 0.5 to 1.5 percent of it on the first pass, so one percent is the middle of that range rather than the top of it. Netra reads every invoice line against the contract that governs it, on every line rather than a sample, and shows its arithmetic on every claim.
Four weeks, no fee, one analyst of your time. Read-only access to 90 days of invoices and the contracts covering your top 40 vendors by spend. At the end you get a findings report: what we found, what it is worth, and what we got wrong. If it finds nothing material we will say so in writing and drop it.
Put your own spend in. The arithmetic is one multiplication.
The rate is borrowed, not measured on you. Recovery audits report 0.5 to 1.5 percent on the first pass over unchecked spend, with duplicate payments alone at 0.1 to 0.5 percent. We lead with 1 percent, the middle of that range. The low column below is the floor, and we would still take a pilot that landed there.
Four sectors, because the leak has a different shape in each.
The nine rules are the same everywhere. What differs is which vendors matter, how they price, and which of the rules earns its keep. These are the sectors where Decision Minds already runs the data platform, so the vendor list and the chart of accounts are not new to us.
Banks and credit unions
Core processing, card and network fees, bureaus, appraisal, title, flood and document services. Almost all of it prices per unit against volume tiers, so both sides of the comparison are structured data and a rate check is cheap. Mergers are the sharp case: two vendor masters, two contracts at two prices, and overlapping invoice windows for at least a year.
Rules that earn their keep here: R1, R2, R4, R8.
Public sector and agencies
Many buyers, one vendor. The same reseller invoices dozens of departments, each negotiating, receiving and checking separately, and nobody holds one view of what the whole body pays. Published rate cards and statewide price agreements make the comparison unusually clean once the contract side is loaded, and published spending files make the vendor graph checkable from outside.
Rules that earn their keep here: R1, R3, R7.
Platforms and marketplaces
Payment processing priced per transaction with a dozen fee components, fraud and identity services, outsourced support and trust operations, and cloud that scales with traffic rather than headcount. Volume moves faster than the paperwork, and tier thresholds get crossed months before anybody re-reads the schedule.
Rules that earn their keep here: R2, R5, R9.
Data and AI heavy enterprises
Warehouse credits, model and inference spend, non-production environments nobody switched off, seat tiers bought for a headcount that has since moved twice. This is where our hand is strongest, because we run these platforms day to day and already know what normal consumption looks like on them before the invoice arrives.
Rules that earn their keep here: R1, R2, R8.
Five categories, ranked by where we look first.
These are the places this leaks in the organizations we work in. Whether any of them leak at yours is unknown to us until we read your invoices. Each card carries the mechanism, a published benchmark, and how far we trust that benchmark. The weak ones are tagged weak.
1 · Software, cloud and licenses
Best evidenceConsumption billed against a committed rate that changed at renewal, non-production environments nobody switched off, seat tiers bought for a headcount that has moved twice since, and escalators applied a quarter early. Usage is metered on one system and priced on another, and the two are almost never compared.
Those measure waste, not billing error. We model 5 to 12% of the line as recoverable, well under both.
2 · Professional and outside services
Usually the largest lineConsultancies, legal, audit, staffing and outsourced operations. Hours invoiced against hours delivered, rate changes applied before the amendment date, work billed past the end date of the statement of work that allowed it. The largest third-party line in most organizations, and the one with the loosest paperwork.
We apply the lowest rate we hold to the whole line rather than guess at the mix inside it.
3 · Duplicate and re-keyed payments
VerifiableThe same charge paid twice, usually days apart, usually after a system change, an acquisition, or a vendor re-issuing an invoice under a new number. The two payments look different in the ledger and identical on the bank statement.
This is the one category where the finding is not arguable. Either it was paid twice or it was not.
4 · Telecom, connectivity and per-unit services
Easy to checkCircuits billed after they were canceled, per-seat and per-transaction fees against volume tiers, surcharges added between one bill and the next. Everything here prices in fractions of a cent per unit, which is exactly the arithmetic people stop doing.
We hold no separate published benchmark for this category and use the same 0.8 to 2%.
5 · Charges no contract covers
Most common, weakest claimA line arrives from a vendor you hold no current terms for, or under terms that expired. This is the most common thing an audit finds and the worst thing to bill for, because the usual answer is that a term exists and nobody filed it.
Rule R7 below is the one doing that, and it is the shape we copy for anything uncertain.
What we are not claiming
Read this oneWe have not seen your invoices. Every number above comes from a benchmark somebody else published or from a public payment file, and we have said which is which. The sample set in the workspace is synthetic and wrong on purpose.
Read-only. Nothing writes back without a person approving it.
Netra does not replace your ledger or your approval workflow. It reads them and puts a verdict next to each invoice before your approver sees it.
Pull the evidence
- Invoice lines and the approval trail
- Contracts, order forms, rate cards
- Usage and consumption logs
- Vendor email threads
Build the context graph
- One vendor identity across every spelling
- Contract clause to billed line
- Every prior invoice from that vendor
- What another division paid for the same thing
Decide, with evidence
- Pay, hold or dispute, with a reason
- Confidence on every call
- Citation to the governing clause
- Low confidence routes to a person
Only what you allow
- Drafts the dispute, attaches the evidence
- Goes out after a person approves it
- Posts the verdict back to AP
- Reports alongside the rest of your data
Nine checks. All of them arguable in front of the vendor.
Nothing here rests on a pattern in the data. Every one of these is a term you signed set against a number you were billed. Each is a comparison you could do by hand if you had the time, run against every line instead of a sample.
| Rule | What it compares | What it claims |
|---|---|---|
| R1 | Billed unit price against the contracted rate on that date | The excess over the ceiling |
| R2 | Quantity billed in a period against the cap | The units above the cap, at the contracted rate |
| R3 | Invoice date against the start and end of the term | The whole line, since no term was in force |
| R4 | Same charge, same amount, twice inside three weeks | The second one |
| R5 | Billed price against the rate after your discount | The discount that was not applied |
| R6 | Tax charged against an exemption on file | The tax |
| R7 | A line against every term you hold | Nothing. It asks which term covers this. |
| R8 | A price rise against the increase the contract permits | Only the part above the permitted ceiling |
| R9 | Quantity times unit price against the line total | The difference, when the line does not foot |
The hard part is the context graph, not the arithmetic.
Anyone else starts at zero
A recovery audit firm spends its first two quarters learning your vendor list, your entity structure and your chart of accounts. That discovery is most of the product. On the accounts where Decision Minds already runs the data platform, it is done.
Data modeling before finance
Resolving one vendor across several spellings, two ledgers and a decade of contract history is a data problem first. That is the work Decision Minds does, and Netra is what we built on top of it.
Contingency is a bad incentive
Paying an auditor a share of what they claim gives them a standing reason to claim too much. We price the ongoing read as a subscription and cap any share of recoveries. Findings you cannot take to a vendor are worth nothing to either of us.
The limits matter more than the claims.
It does not send anything
There is no mail integration and no vendor portal. The disputes tab writes text. A person reads it, edits it, and sends it from their own mailbox, or does not.
It holds back what it is unsure of
Every finding carries a confidence. Below the line it never reaches a draft. It goes on a list for a person to read. A duplicate charge and a genuine repeat order look identical in a CSV, and the engine says so instead of guessing.
It claims nothing on a line no term covers
A charge outside every contract you hold is the most common thing an audit finds, and the weakest thing to bill for. Netra reports the amount at risk and asks which term governs it. That is a question for your vendor manager, not a claim.
It does not upload your data
The workspace runs in the browser. There is no upload endpoint and no database behind it. The server serves files and checks a token, and that is the whole of it. Clearing site data clears the workspace.
It is only as good as the terms you give it
Rates, caps and discounts have to be stated. Netra does not read contracts out of PDFs today, so somebody types the commercial terms in once per vendor. That work is the product.
Four weeks, no fee, one analyst of your time.
Read-only export of 90 days of invoice history and the contracts covering your top 40 vendors by spend. We build the vendor graph.
Netra reads every invoice in the window against its governing contract, rate card and usage record. Findings start stacking.
Your team triages the first findings with us. False positives tune the thresholds. We throw out what does not hold up.
Findings report: what we found, what it is worth, what we got wrong, and a read on whether the full build is worth it to you.
What is fact, what is borrowed, what is ours.
| Claim on this page | Status | Where it comes from |
|---|---|---|
| 0.5 to 1.5% recovered on a first pass over unchecked spend | Published | Recovery-audit industry range. Measured on other organizations, not on you. |
| Duplicate payments at 0.1 to 0.5% of AP spend | Published | Recovery-audit industry data for a settled organization. |
| 29% wasted cloud spend, ~46% unused software seats | Published | Flexera 2026 State of the Cloud; Zylo 2026 SaaS Management Index. Both measure waste, not billing error. |
| 1% as the headline rate | Our choice | The middle of the published first-pass range. Not the top, and not measured on you. |
| $1,000,000 a year on $100M of spend | Arithmetic | 1% of the figure in the box. Nothing else is in that number. |
| Deferred years worth the same as year one | Weak | We hold no separate rate for deterrence. Applying the recovery rate is a placeholder and probably low. |
| The workspace sample set | Invented | We wrote those vendors, invoices and contracts ourselves, wrong on purpose, to show each rule firing. |
The sample set is loaded and wrong on purpose.
Six vendors, twenty-two lines across thirteen invoices, five contracts. Every rule fires at least once, two invoices come back clean, and one vendor has no contract at all. Work it, then paste in a month of your own.