You have pay gaps you cannot defend. Close them with the money you are already spending.
HyperEquity folds pay-equity correction into the merit allocation itself — so the gap closes inside the cycle, not as a separate remediation project with its own budget request.
The Real Problem
The module handles workflow. It does not handle the maths.
Almost every large organization already owns a merit tool. Almost every one of them still opens Excel halfway through the cycle.
The pattern is consistent: launch in the HRIS module, discover it cannot model the budget the way your philosophy requires, export to a spreadsheet, do the real work there, and load the answers back in. The system of record ends up recording a decision it did not help you make.
Meanwhile the gaps that need closing — two people in the same job, same tenure, same rating, hundreds or thousands of dollars apart for reasons nobody can articulate — get handled, if at all, in a separate remediation exercise that has to be funded and defended on its own.
HyperEquity was built by a compensation practitioner of twenty-five years specifically to collapse those two problems into one pass.
The Engine
What the algorithm actually does
Budget allocation, to the dollar
Finance hands you a number. HyperEquity pushes it down through the organization — by country, division, and manager tier — and then all the way to the individual, weighted by performance and position in range. Give India 14% and the US 3.5% and each pool resolves independently. Every dollar lands, and the total is exact.
Pay equity, inside the cycle
The engine finds pay differences between comparable employees that your own policy cannot justify, and prioritizes them in the allocation. A top performer sitting below midpoint gets moved further than an identical peer already above it. The gap closes as a consequence of running merit properly — not as a line item you have to go and ask for.
Built For
The parts that only matter at scale
Multi-country budget pools
Deep manager hierarchies
Defensible reasoning per employee
Audit trail and multi-level approval
Evaluating
You do not need an integration to judge this
A full SFTP integration takes 4–5 weeks, and that is a reasonable thing to schedule once you have decided. It is an unreasonable thing to ask of an evaluation. So start with a CSV: export a census, load it, and see the engine reason about your own population in an afternoon. Integrate afterwards, if and when it makes sense.
Questions
What compensation leaders ask us
Because most teams running a merit module still export to Excel to model budgets and correct pay gaps, then load the results back in. HyperEquity does that modeling inside the tool. If your team never leaves your HRIS during merit, you may not need us — if you do, that round trip is the thing we remove.
HyperEquity looks at employees in comparable roles with comparable tenure and performance, and identifies pay differences that your own policy cannot explain. Rather than treating remediation as a separate project with its own budget, it folds the correction into the merit allocation, so the gap closes using money you were already spending.
Yes, and this is a core capability rather than a workaround. Set India at 14% and the US at 3.5%, and each pool allocates independently across its own population by performance and range position, down to the dollar.
Always. HyperEquity produces the recommendation and the reasoning; managers can adjust within the guardrails you set, with live budget tracking and inline policy warnings. Approvals are multi-level with a full audit trail.
Around 4–5 weeks over SFTP, with most of the effort on our side. You do not have to wait for it to evaluate — start on the CSV path in 5 days and integrate later if you want to.
A full configuration and detailed recommendations for up to 10 employees, with exports disabled. It is enough to see how the engine reasons about your own population without us handing over the algorithm.
Smaller organization without a comp team? Start here instead.