Your business is always spending. Brain is always thinking.
Enterprise spend intelligence is software that measures how well a company spends — not how much. It reads every transaction against your own policy and contracts, prices each gap in đồng, and writes the fix back into the systems your team already uses.
Vietnamese and multinational enterprises already running on Xperise.
Most finance stacks are built to record spend accurately. Enterprise spend intelligence is built to judge it — continuously, against a standard, in money.
Targets are derived from your own policy and contracts, so the benchmark is defensible inside your own business.
Every gap carries a đồng value and the arithmetic that produced it. Finance can check the working.
The decision leaves as a control in the Policy Engine, the Marketplace and Expense — then Brain measures itself.
You cannot fix that by travelling less — the cost of each unit is what is moving. Which makes how well you buy the only lever left that scales.
// $1.71 trillion on 1.84 billion trips in 2026, up from $1.59 trillion in 2025. Source: GBTA Business Travel Index, August 2026.
Global business travel spend forecast for 2026, on track to pass $2 trillion by 2030.
GBTA BUSINESS TRAVEL INDEX · AUG 2026Of finance professionals now use AI, up from 17% in 2023 — still the lowest adoption of any business function.
CFO CONNECT · STATE OF AI IN FINANCE 2026Of CEOs report AI has delivered both cost and revenue benefit. Investment is not the constraint; redesign is.
PWC GLOBAL CEO SURVEY · JAN 2026Of negotiated savings lost to off-contract buying. World-class teams leak 60% less than their peers.
THE HACKETT GROUPEvery screen on this page is one of these four steps, running on the category you selected above. Change the category and the whole loop rebinds.
Brain sits inside the Spend OS, so a booking, a receipt, a card swipe and a contract line all land as one record — with the trip, the department, the policy and the supplier already attached.
Six economic levers measured against targets read from your own policy, your own contracts and your own 12 months — so only what crosses a threshold reaches you.
// Bar widths on a log scale. The rest were filed and closed without you.
Brain does not stop at the number. It opens the drivers, so the conversation starts at the cause.
A recommendation you cannot audit is an opinion. Select a lever — the arithmetic, the scenario below and the rule that gets written all follow it.
Every control has a cost somewhere else. Brain models the trade before you sign it — and carries the result straight into the rule below.
// Modelled on your own last 12 months.
This is where spend intelligence separates from analytics. The decision leaves as a rule, with an owner, a date and a success measure attached.
Expected annual impact · owner named · success measure attached · review in 12 weeks.
Select any row to run the whole page on that category. One model, one memory, one place to ask.
| Spend category | Collect | Monitor | Optimize | Control | On the table |
|---|---|---|---|---|---|
| Travel | |||||
| Expense | |||||
| Corporate Cards | |||||
| Operational Spend | |||||
| Employee Spend | |||||
| Procurement |
Four pools of value, each with an independent benchmark and the lever on this page that goes after it. Where no credible external benchmark exists, the row says so rather than filling the gap.
Of negotiated savings lost to off-contract buying, across categories.
THE HACKETT GROUPOf indirect spend sits outside contract. World-class teams leak 60% less.
THE HACKETT GROUPReduction in purchase-to-pay process cost when the process is redesigned around AI — not merely automated.
HACKETT · AI WORLD CLASS PROCUREMENT · JUL 2026No credible external benchmark. Measured on your own payment terms and daily run-rate.
NOT BENCHMARKED// Benchmarks are industry-wide and independent of Xperise. The đồng figure is computed from the model on this page — every lever opens its arithmetic.
Bring one category and 12 months of history. We will show you the levers, the arithmetic, and what it would be worth to fix.