No Pay Request Left Waiting
The agent flags employees paid below their pay-grade minimum, and approvers are reminded of change requests that wait past your reminder window. Read-only for employees.
HOW IT WORKS
How it keeps the comp cycle on track
From "below band" to "admin alerted" — using the pay grades you already maintain. It finds the gap before the comp lead has to go looking for it.
1. Detect
An employee's pay sits below their pay-grade minimum. The loop finds it on its own sweep, before the comp lead has to look.
2. Decide
Counts the employees below their grade minimum — read-only; it never changes anyone's pay. The same alert repeats at most once a week.
3. Act
Alerts the business admins, with a link to Analytics — automatically when trust is high, queued for sign-off when the level is lower.
4. Log
Every alert lands in the agent's activity log with how many admins it reached. Audit-defensible evidence ready by default.
AUTONOMY YOU CONTROL
Three levels of autonomy. You pick.
Start with it off — it surfaces suggestions but takes no action until you say so. Move to approve for a one-tap checkpoint on every action. Let it run on its own when you're ready.
Off — manual only
Nothing fires on its own — below-band findings just surface on the comp console for the comp lead to act on.
Approve
It queues each below-band alert for a one-tap send by the comp lead. The pending queue is your morning standup.
Auto
It sends below-band alerts automatically. Higher-impact escalations still come back to you.
Every automated nudge says what it is about
When autonomy is on, the agent counts the employees paid below their pay-grade minimum and tells admins how many there are, so a band problem surfaces before review season. Approvers with requests waiting get one reminder that counts every request still waiting on them and links to the queue, and it closes itself when the last one is decided.
- Below-band alerts — how many employees sit under their pay-grade minimum, sent to admins.
- One approval reminder per approver — every waiting request counted in one card, closed when the last is decided.
- Pay never changes on its own — every pay change waits for a person allowed to make it.
One console — comp's home for cycle autopilot
The AI Comp Reviewer console is the buyer-facing landing for comp leads and HRBPs. Pending- recommendations count sits front and center with a per-cycle sparkline. The "What the AI handled" feed shows the most recent actions across reviewers. The "AI actions to approve" list surfaces approval-gated final numbers.
- Hero metric + trend — pending recommendations + throughput sparkline.
- "What the AI handled" feed — the most recent reminders, nudges, and flagged outliers.
- "AI actions to approve" list — approval-gated final numbers approved or rejected inline.
- Autonomy dial — Off, Approve or Auto, set on the console.
Why Pay Conversations Are So Painful
AI Comp Reviewer gives every employee a clear, grounded view of their own pay — so the conversations HR has are the ones that actually need HR, not the ones that just needed a number.
Employees Guess At Their Pay Band Placement
They know their salary. They don't know whether it sits at the 25th, 50th, or 75th percentile of their band. Without that context, every market article and Glassdoor post becomes a source of anxiety — and a ticket to HR.
Annual Review Timing Is A Surprise
The employee thinks their review is "in March." HR has them on an October cycle. By the time it comes up, the employee has been silently expecting an adjustment that wasn't coming. Calibration conversations get harder than they had to be.
Compensation History Is Scattered Across Offer Letters
To answer "how has my pay changed over time?", the employee has to dig through three years of offer letters, merit notes, and email PDFs. The data exists in the HRIS — but it's buried under a tab in a tab in a tab.
Bonus Eligibility And Targets Are Verbal Folklore
"I think I'm eligible for a 15% bonus, paid in March, but it might be quarterly?" Pay plans live in the recruiter's head and a PDF nobody re-reads. When the bonus shows up, it's a surprise — for better or worse — and that's not how compensation should work.
Total Comp Calculations Never Include The Pieces That Matter
Base salary feels like the whole number, but the real picture includes equity vesting, bonus target, 401(k) match, ESPP, and the benefits load. The employee comparing a competing offer doesn't have a clean breakdown of what they actually earn — so they undersell their own package, or worse, accept an external offer that's $30k lower in total value.
Review Dates And Bonus Targets Are A Black Box Until They Hit
Two years in, an engineer starts wondering — when is my next compensation review, am I in the bonus plan, what is my target? Without grounded answers about their own review date and bonus eligibility, the best people start interviewing externally to figure out their own worth, and the company finds out too late that retention was the conversation that never happened.
AI Comp Reviewer At A Glance
AI Compensation
Your own pay in plain language, and below-band equity alerts for admins.
Inside AI Comp Reviewer — The Actual Capabilities
Every block below maps to a real tool the agent uses against the employee's compensation record. Read-only for employees — a pay change is offered only to people allowed to change pay, behind a confirmation.
"What Am I Paid Right Now?" — Grounded And Specific
The most common compensation question, answered without an HR ticket. The agent surfaces base salary, pay type, and pay grade — and, when your organization shows pay-band position, range placement and compa-ratio, so the employee knows where the number sits inside their band.
- View current compensation — base salary, hourly rate, pay type, and pay frequency.
- View pay grade summary — the grade, plus compa-ratio, range penetration, and quartile when your organization shows pay-band position.
- Range placement — where in the band the employee sits, with quartile context, under the same setting.
- Permission-aware — employees only see their own compensation; the agent does not expose peer comp.
How Your Pay Has Changed Over Time
Every salary change in one place, with the reason and the direction. The employee doesn't have to dig through offer letters and merit notes to reconstruct their pay history — it's all on the record, and the agent surfaces it on demand.
- View compensation history — your recorded salary changes, most recent first (up to 50 per request), with effective dates and reasons (merit, promotion, market adjustment, etc.).
- View last compensation change — the most recent change with its direction (increase or decrease, where the record shows both figures) and reason.
- Compare current to previous — your current pay beside the figures before the most recent change.
- Compensation summary — tenure, total change history count, and high-level trajectory at a glance.
Next Review Date And Bonus Eligibility
Two questions that drive most "I'm thinking about my pay" conversations — when's the next review, and what's my bonus target? Both asked in chat and answered from your record: the review date where your organization keeps one (otherwise your hire anniversary, labelled as such) and your bonus plan.
- View next review date — the review date your organization has set; when none is set, the agent says so and gives your hire anniversary instead.
- View bonus eligibility — is the employee in the bonus plan, and what's the target percentage.
- Read-only — the agent surfaces dates and targets; reviews and bonus payouts happen in the Compensation app.
Outcomes Teams Can Measure
The agent's job is to make pay transparent without adding work for HR — to absorb the questions that were already on the HRIS and free HR for the conversations that require a human. Measure against your pre-agent baseline.
- HR comp-question deflection — pay, history, and review-date questions absorbed by the agent vs ticketed to HR.
- Pay transparency score — share of employees who can correctly state their pay grade placement (survey instrument, comparable across cycles).
- Review-cycle visibility — share of employees who know their next review date within 30 days of accuracy.
- Bonus understanding — share of bonus-eligible employees who know their target percentage and payout window.
- Off-cycle adjustment volume — comp inquiries that escalated to off-cycle reviews because the original question had no clear answer.
Read-Only For Employees
For an employee, AI Comp Reviewer retrieves and explains — it has no tool that changes their compensation record. The employee sees their own pay through the agent because the tool query is scoped to them. Pay figures the agent reads are scrubbed from the stored AI logs.
- No write tools for employees — updating pay is offered only to people your organization lets change pay in the Compensation app, and approving or rejecting a change request only to admins, each behind a confirmation.
- Permission-aware — employees see only their own compensation; no peer visibility, no manager-view shortcuts.
- Pay figures scrubbed from AI logs — salary, hourly rate, and pay-change figures the agent reads are removed from the stored AI log entries.
- Audit trail on every retrieval — every lookup logs the requesting user and which tool ran.
WHAT TEAMS TRY INSTEAD
The four alternatives — and why none of them give THIS employee a grounded view of their own pay
HR and total-rewards teams trying to drive pay transparency usually try one of these four. None of them combine band placement (where your organization shows it), change history, bonus eligibility, and review timing in one grounded conversation.
Pasting offer letters and Glassdoor pages into ChatGPT, Claude, or Copilot
Employees stitching their own comp story from scattered documents
- The agent reads the employee's actual HRIS record — change history, bonus plan, and band placement when your organization shows it
- Pay figures the agent reads are scrubbed from the stored AI logs — not left in a public chat tool's history
- Scoped to the employee asking — the pay-lookup tools take no other person's name or id
Pave AI / Lattice Compensation AI / Workday Comp Advisor
Vendor-trapped compensation AI inside one HRIS or compensation platform
- Composes with Performance, Payroll Assistant, Headcount Planner, and Offer Manager — not stuck inside one comp surface
- Available to every employee, not just HR business partners on a vendor seat
- No second per-employee AI license on top of the comp-tooling contract
A custom comp-transparency chatbot
An engineering team's six-month build, then forever maintenance of the audit trail and access rules
- Shipped already. Engineering spends zero weeks plumbing band placement, change history, or review timing
- Read-only for employees on their own record; pay changes sit behind a role gate and a confirmation
- Inherits new capabilities as the platform evolves
The manual fallback — "ask your manager or HR business partner"
The default when pay questions surface
- Band-placement and next-review-date questions self-serve — HRBPs handle the calibrations that actually need them
- Bonus eligibility and next-review dates stop being verbal folklore
- Compensation history is one query away, not a three-year offer-letter archaeology project
PLATFORM ADVANTAGE
AI Comp Reviewer inherits everything the platform already runs
A standalone comp bot has to plumb each of these. AI Comp Reviewer gets them for free because Performance, Payroll, Headcount, and Offer Manager already do.
Cross-app data plane
Current pay, pay grade, change history, review date, and bonus eligibility all reach the same agent — no separate analytics export.
Strict permission model
Employees see only their own compensation — no peer visibility, no manager-view shortcuts, no "let me check yours" path. The agent inherits the same boundary the comp app enforces.
Pay figures kept out of AI logs
Salary, hourly rate, and pay-change figures the agent reads are scrubbed from the stored AI log entries.
Audit trail on every retrieval
Every lookup logs the requesting user and which tool ran — useful for HR compliance and pay-equity audits.
Provider-agnostic model tiering
The platform assigns each agent one model tier suited to its work — set for the agent, not picked per question.
Confirmation on every pay change
Updating pay and approving or rejecting a change request each ask for confirmation first, and are offered only to people allowed to act on pay.
INDUSTRY FIT
Industries where pay transparency moves retention and trust the most
AI Comp Reviewer helps wherever a knowledge-heavy or pay-band-driven workforce is comparing internal pay to the market.
Technology
Engineering and product talent get grounded band placement and next-review-date answers instead of interviewing externally to "figure out their worth."
Financial Services
Bonus-heavy roles get clarity on plan, target, and payout timing; pay-equity audits get a defensible audit trail.
Healthcare
Clinical staff understand shift differentials, on-call premiums, and bonus eligibility without HR Q&A backlog.
Professional Services
Billable-utilization-tied bonus structures, and promotion bands become transparent to every consultant.
Public Sector
Step-and-grade systems become self-serve queryable, with full audit logs.
Multi-Regional Enterprises
Employees across regions see their own pay band, market context, and change history without exposing peer or cohort data.
WHY MANGOAPPS WINS
An embedded agent beats a chatbot, a vendor add-on, or a custom build on every axis
The argument finance, security, HR, and total-rewards all share — and the one a single-vendor comp-platform AI structurally cannot answer.
Cheaper than the alternatives
No per-seat ChatGPT license, no Pave AI subscription, no Lattice Comp AI tier, no Workday Comp Advisor add-on, no six-month custom build.
More secure
Read-only for employees on their own record. Pay figures the agent reads are scrubbed from the stored AI logs. AI requests go to the platform's configured model providers, like every MangoApps agent.
Easier to deploy
Already deployed if you have Compensation enabled. Turn the agent on against the existing HRIS comp record and it's running the same day.
Easier to use
Lives inside Ask AI — no separate comp portal, no offer-letter archaeology, no "let me check with HR" delay.
Easier to manage
Band visibility and employee self-view settings sit in the same admin console as every other app. One audit log, one access model.
Easier to extend
Shares the agentic tool framework with every other MangoApps agent. New comp slices (deferred comp, RSU refresh, geo-differentials) ship as tools, not rewrites.
AI is actually better
A vendor comp AI can show a band chart. AI Comp Reviewer gives the employee their change history, bonus eligibility, and — when your organization shows it — band placement in one grounded conversation.
At our head office within HR, marketing, and finance, we use ChatGPT quite a bit, and MangoApps AI Helper is a useful tool for us. As I go around to the stores, I’ve been showing them how the AI Intranet Helper can find things and answer plain language questions about our resources, and they’re quite excited about that.
Alison van Zijl
Head of Human Resources
Full House
Customer Success
MangoApps Customers
Organizations that trust MangoApps to run every workflow across their workforce.
Customer Case Studies
Customer Case Studies
Customer Case Studies
Customer Case Studies
Customer Case Studies
Customer Case Studies
Frequently Asked Questions About AI Comp Reviewer
8 read-only tools for employees — view current compensation (salary, pay type, rate), view full compensation history, view next review date, view compensation summary (tenure + change count), view last compensation change with reason and direction, compare current to previous compensation, view bonus eligibility and target percentage, and view pay grade summary (grade, plus compa-ratio and range placement when your organization shows pay-band position). Admins also get tools to list overdue reviews and pending change requests, update pay, and approve or reject a request — each write behind a confirmation.
Not for an employee — the tools an employee gets retrieve and explain; none of them changes compensation records, moves review dates, or modifies bonus targets. People allowed to change pay in the Compensation app can ask the agent to update an employee's pay, and admins can approve or reject a pending change request; each asks for confirmation first.
No. The agent is scoped to the employee asking, about their own compensation. There are no peer-comp tools and no manager-view shortcuts for direct reports' pay. Aggregate market benchmarks and offer-comparison tools live in Offer Manager Agent — for recruiters, not employees.
Compensation data is sensitive. The employee sees their own data because the tool's database query is scoped to them. Pay figures the agent reads are scrubbed from the stored AI logs. AI requests go to the platform's configured model providers.
HR comp-question deflection, pay transparency score (survey-based), review-cycle visibility, bonus understanding, and off-cycle adjustment volume. Compare against your pre-agent baseline.
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Why Choose Us?
- Frontline AI: Governed AI for every employee and workflow.
- Top Security: HITRUST, ISO & SOC 2 certified.
- Exceptional UX: Delightful on mobile and desktop.
- Proven Results: 98% customer retention rate.
Rolled out to every employee at AutoZone (125,000), PetSmart (50,000+), A.S. Watson and Raley's (20,000) — and at larger retailers we are not permitted to name.
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