Frequently asked questions.

No. AddUp integrates with the system you already use for employee records, org structure and payroll, and adds what that system doesn't cover: designing and calculating variable pay, pay equity, weighted goals, employee experience and performance, all connected.

Yes. AU Rewards works with the market survey your organization already licenses, whether from a global consulting firm or a local survey, for salary bands, positioning and equity. That data is used only for your organization. Before loading it, check that your license allows its use in a third-party tool.

The whole workforce. AU Rewards calculates goal-based bonuses, P×Q commissions, mixed schemes, discretionary bonuses and raises, with different schemes running side by side in the same organization, and keeps an audit trail for every calculation.

No. Payroll processing stays in your payroll system. AU Rewards designs and calculates each variable pay item, routes it for approval and delivers the inputs per person and per item, ready for payroll.

Yes. You can design a different scheme for each employee group (operations and administrative staff, union and non-union employees, or however your company organizes its workforce), each on its own calendar: monthly, quarterly, every four months, semiannual or annual.

Yes. You can start with AU Rewards, AU Goals, AU Employee Experience or AU Performance. When you add another module, AddUp connects the data you already have, with no re-entry.

In a spreadsheet, every calculation depends on whoever builds it, and the history gets lost from one cycle to the next. In AddUp, calculations are automatic and traceable, you can simulate before you apply, every payout goes through approval with role-based permissions, and pay is read alongside each person's goals, performance and experience.

Yes. AU Goals works with OKRs, weighted KPIs or a combination with skills, depending on how each organization runs goals.

The annual survey, pulse surveys and journey surveys, such as onboarding or exit, plus comment analysis. Every survey ends in action plans by leader and a follow-up measurement that shows whether the action worked.

An annual engagement survey takes a snapshot of the organization once a year. Continuous listening adds pulses and surveys at key moments of the journey, such as onboarding or exit, reads the results alongside the same team's pay, goals and performance, and measures again to see whether the action improved engagement and retention. If you run an annual survey today, AU Employee Experience uses it as the starting point.

Yes. AU Performance includes self-assessment, feedback and 180° and 360° reviews, along with potential, calibration, succession and development plans.

Whichever your organization uses. AU Performance builds the talent map as a 9-box or a 4-box, on the axes your methodology defines: performance and potential, or competencies and skills crossed with goal attainment. The name of each box follows your model too.

Between 2 and 4 weeks. The timeline depends mainly on the organization sharing the required information and meeting the technical requirements to use the platform.

With the HRIS and payroll systems your organization already uses, via API, SFTP or unified connectors.

Yes. Through MCP, the open standard for connecting AI assistants, each person can query AddUp results, reports and plans from the assistant their organization uses, such as Claude, ChatGPT or Copilot. They see exactly what they see in the platform, never more: the same permissions apply, the assistant can only read and never changes data, and every query is logged.

No. Implementation is guided: it includes migrating your existing schemes and data, configuration that follows your organization's practices, and expert support. Ongoing support is included.

AddUp can be used in any country. The platform is multilingual and multi-currency: it calculates salaries, bonuses and raises in the right currency and brings local context, such as inflation, into salary reviews.

In cloud infrastructure, encrypted in transit and at rest. Analysis happens inside the platform: you don't need to move your data to an outside chat to work with it.

Each person sees what their role allows. Your organization defines the permissions, and access and changes are logged.

Our SOC 2 certification process is underway.

No. In pay and performance, the AI recommends and a person decides. Every decision is logged with the reasoning behind it.

No. Neither AddUp nor the AI provider we use trains models on your data.

Always a person. No agent makes decisions that affect people on its own: its recommendations go through approval and are logged, with the factors behind them in plain view.

We audit for bias regularly, especially in performance and pay, to detect whether a recommendation treats people differently based on gender or age. And in those decisions the AI recommends, but a person always decides.

Before any information is sent to the AI and before any report is published, AddUp masks sensitive data such as names or health information.

Every model change first goes through an automated evaluation set that checks answer quality. The architecture also allows switching providers if needed.

No. At AddUp, survey comments are always data, never instructions, and we test manipulation attempts before every release.

Per module, based on the number of people covered by each one, with no minimum number of modules. Guided implementation and support are included. Book a demo for a quote.