Anonymous by architecture
Reviews and salary reports are stored decoupled from member identity, with one-way hashing, so anonymity survives scrutiny.
AI-Built Glassdoor Clone
An AI-first build of every transparency mechanic: moderation screening that protects content trust, salary outlier detection that keeps ranges honest, and sentiment analysis that turns reviews into insight employers pay for. Three synced panels ship white-label with 100% source code. The almost-ready AI build goes live in 6 working days; a custom build takes 3 to 4 weeks.
Launch-ready from
$2,499

Synced panels
Almost-ready AI launch
Custom build
Source-code ownership
Canonical Moxace facts behind every build.
overview
An employer review platform is a community where current and former employees anonymously review companies, report salaries, and describe interview experiences, and where job seekers research employers before applying. The Glassdoor-style model pairs user-generated transparency content with job listings and employer branding products.
The purpose is to inform job decisions with data workers cannot get anywhere else, and the business logic follows the audience: review traffic converts to job applications, and employers pay to claim profiles, respond publicly, and present their brand to candidates who are already researching them.
A complete build includes the member app, an employer panel for claimed companies, and an admin console, over a moderation pipeline, salary bucketing with outlier suppression, and anonymous identity architecture that keeps review authorship protected.
Employer transparency content has become a standard part of job research in most professional markets, and review platforms persist across industries, geographies, and seniority levels. Treat market figures as directional; the structural point is that content trust, not feature count, is the entire product, and trust is an engineering property.
The headline layer above the per-panel detail.
Reviews and salary reports are stored decoupled from member identity, with one-way hashing, so anonymity survives scrutiny.
Submitted salaries normalize into role, seniority, and city buckets with outlier suppression, so one bad entry cannot skew a range.
Automated policy screening plus a human review queue with reports and appeals, auditable end to end.
A claim workflow that verifies company ownership before employers access response and branding tools.
Role-specific interview questions and process descriptions that attract candidates in active job search.
Push alerts on new reviews and openings for followed companies, driving repeat sessions.
Listings shown alongside ratings and salary bands, converting research sessions into applications.
What these buyers share: an audience that researches employers, and the intent to own the trust layer they read.
Build the transparency layer incumbents ignore for an industry or region, with moderation tooling that protects the trust from day one.
Add community content that feeds your existing recruiting products, with salary data as the proprietary asset competitors cannot scrape.
Run member-driven review platforms in your sector, where the community already trusts the messenger.
Convert workplace audiences into a data asset, with sentiment analysis making the content quotable and advertisers interested.
Pair listings with reviews, because research content is what brings candidates back between application cycles. Pairs naturally with our Indeed-style job board.
Three products, one transparency community. Every panel ships in every build.
The community experience that generates your content moat.
Branding and response tools for reviewed companies.
Trust is your product; moderation is how you keep it.
Four consoles, one view of companies, moderation, and money.
Company record management with duplicate employer merging, the claim verification workflow, and profile oversight across the two-sided engine.
The moderation queue with screening assist, content policy rule engine, report and appeal handling, and audit trails on every action proving good-faith process.
Salary outlier detection and bucket administration, fake-review pattern monitoring, and category and taxonomy tools keeping the corpus searchable.
Employer package and subscription administration, featured-placement sales, recruitment analytics upsells, and revenue reporting for finance.
The community loop that turns anonymous insight into job traffic.
A current or former employee submits a company review, salary report, or interview experience, verified against employment details.
Submissions pass automated checks and a human queue against community guidelines before anything publishes.
Approved reviews and salaries appear on the employer profile, aggregated into ratings and percentile ranges.
The company posts a public response and can claim the profile to add facts, branding, and open roles.
Candidates read reviews and salary bands alongside listings, then apply to the company's open jobs in the same session.
Profile traffic, application volume, and brand ratings become the renewal argument for the employer's subscription.
Five model-driven systems working the same content stream. Each ships pre-tuned for review platforms and sharpens as your data compounds.
Pre-screens every submission for policy violations, defamation risk, and manipulation patterns before the human queue sees it.
Review text, submission metadata, account and report history
A review queue your team can clear without letting bad content through
Catches implausible salary entries before they skew published ranges, keeping the data employers and candidates both rely on honest.
Submitted salaries, role and city context, distribution shapes
Salary bands candidates trust and employers cannot game
Tags reviews by theme, from management to compensation to culture, so employer analytics pages sell themselves.
Review text, ratings, theme co-occurrence
Employer subscriptions with analytics worth paying for
Learns coordinated-submission and incentivized-review patterns so your ratings survive the first attempt to game them.
Submission timing, account graphs, review similarity
Ratings that hold up under employer and candidate scrutiny
Ranks the companies and reviews each member sees from their industry, role, and follow graph.
Browsing history, follows, role and location signals
Deeper sessions and more contributions per member
platform concepts
Moderation is the product. Contributions move through submitted, screened, approved, disputed, and removed states, with automated checks catching patterns and a human queue handling the rest, because one fabricated review can cost the platform its entire value proposition.
Anonymity and verification have to coexist. Identities are verified against employment records but never exposed, and aggregated salary data publishes as ranges and percentiles rather than raw entries, which is what keeps contributions honest and contributors safe.
The employer profile is the two-sided engine. Community content attracts job seekers, job traffic attracts employers, employer subscriptions fund moderation, and each side's behavior is the other's supply, so the loop only works if both halves ship together.
Employer branding subscriptions: claimed profiles, branded pages, and response tools sold as monthly packages.
Job postings on top of review traffic: companies with strong ratings buy visibility to hire from their own pipeline.
Featured placement: homepage company spotlights and category sponsorships.
Recruitment upsells: analytics reports on how a company's ratings and salary data compare to its market.
Every package and rate is admin-configurable, so you can price by company size or market without engineering time.
Four groups, each mapped to the part of the review promise it protects.
Contributions moving through submitted, screened, approved, disputed, and removed states, automated checks catching patterns, fake-review detection learning coordinated campaigns, and audit trails proving good-faith process.
Identities verified against employment records but never exposed, submissions stored decoupled from member identity, and employer-side tools seeing only the content and metadata you allow.
Submitted salaries normalized into role, seniority, and location buckets with statistical outlier suppression, market ranges for employers, and distribution context for members.
Claim workflows converting unclaimed companies into the funnel, claimed profiles with response tools and branded pages, job postings riding review traffic, and analytics upsells comparing ratings to market.
insight
Employer review platforms compound on job-board economics: employer branding and recruitment spend keeps compounding past the forty-billion-dollar mark globally by 2030 on widely published forecasts, and review traffic converts to job applications naturally, which is why the two-sided loop funds moderation.
The engineering wedge is moderation and anonymity: one fabricated review can cost the platform's value proposition, and anonymity guarantees have to live in the schema rather than in policy. Operators who ship both earn employer subscriptions on trusted traffic. The revenue table below quantifies the lines.
Six monetization lines across the platform, quantified against published industry benchmarks. Every rate is admin-configurable; the figures here are modelling inputs, not projections of your platform's earnings.
| Criteria | Revenue line | How it is charged | Typical range | What sets the ceiling |
|---|---|---|---|---|
| Employer branding subscriptions | Claimed profiles, branded pages, response tools | Plans commonly $200 to $2,000+ per month | Corpus trust. Plans hold while reviews stay credible | |
| Job postings | Postings sold on top of review traffic | Postings commonly $100 to $500+ each | Traffic quality. Postings scale while the loop stays two-sided | |
| Featured placement | Homepage spotlights and category sponsorships | Placement commonly $500 to $5,000+ per month | Editorial integrity. Placement sells while ratings stay honest | |
| Recruitment analytics | Reports comparing ratings to market | Reports commonly $200 to $2,000+ per month | Data depth. Analytics scale while salary buckets stay rich | |
| Claim funnel conversions | Claimed-profile upgrades per company | Conversions commonly 5% to 15% of claimed companies | Claim quality. Conversions hold while the workflow stays easy | |
| White-label deployments | Branded instances for niche operators | Deployments commonly $10,000 to $100,000+ | Vertical demand. Deals close while per-tenant config stays cheap |
Standard inclusions on every engagement, almost-ready or custom. Nine things you never have to ask for.
The complete unencrypted codebase transfers to you, with documentation and deployment scripts.
Your logo, colors, and store accounts across every panel, plus branded customer communications.
App store and Play Console submissions handled end to end, with production monitoring switched on.
Stripe, PayPal, and regional gateways configured for employer subscriptions and featured-placement billing.
Moderation screening, outlier detection, and sentiment analysis arrive configured for review platforms, not as raw APIs.
Languages, currencies, and tax display configured for your markets during the launch window.
Containerized services on AWS or Azure with autoscaling and queue-backed intake for peak traffic.
Operational dashboards, finance reconciliation views, and CSV exports so your team starts informed on day one.
Included support window plus product updates covering bug fixes, OS compatibility, and version upgrades.
Anonymity, accuracy, and scale are the hard parts. That is where we spend the effort.
Review and salary submissions decoupled from member identity with one-way hashing, so trust in anonymity survives legal scrutiny.
Submitted salaries normalize into role, seniority, and city buckets, with outlier suppression so a single bad entry cannot skew a range.
Automated policy screening plus a human review queue with appeal handling and full audit trails.
Containerized services on AWS or Azure. For custom moderation and trust tooling, see our AI governance consulting practice.
Payment gateways, email and push providers, job-feed imports, and analytics exports ship as configured integrations, so the platform plugs into the tools your operations already run on.
Role-based access, personal-data protection with right-to-erasure workflows, append-only audit logs, and encrypted traffic and secrets come standard, so member-privacy questions have answers before they are asked.
The almost-ready AI build, day by day. Store review times can add a short buffer outside our control.
Markets, content policy, and employer package pricing locked with a written scope, and your identity applied across all three panels.
Payment gateways, moderation rules, salary buckets, and languages configured and tested against your live accounts.
Employer records and taxonomy imported so early users review real companies, then a full pilot: submit, moderate, claim, respond.
App store submissions with review buffers accounted for, production monitoring on, and full launch with post-launch support and product updates included.
Both tracks ship the same trust core. The difference is time, price structure, and how much you want to change.
| Criteria | Almost-Ready AI Launch | Custom Build |
|---|---|---|
| Time to live | 6 working days from branding handoff | 3 to 4 weeks, scoped before work starts |
| Pricing | Fixed written quote after a short scoping call, no hourly meter | Estimated per module after the discovery call |
| Source code and IP | 100% ownership on delivery | 100% ownership on delivery |
| AI layer | Dispatch, forecasting, and personalization pre-tuned for the vertical | AI services designed around your workflows and data |
| Content policy | Proven moderation and anonymity architecture configured on day one | Policy engine and trust tooling designed around your community rules |
| Best for | Operators who want to launch this quarter | Teams with bespoke workflows or a unique model |
| After launch | Post-launch support and product updates included | Post-launch support and product updates included |
$ moxace launch --nowBook a walkthrough and we will demo submission, moderation, and the employer claim flow on a live build, then send the written scope.
Share your idea
a quick call, no deck required
See the live demo
every screen, admin to user
Launch with source
full code, your brand, your servers
No two launches price the same. These are the factors that shape the written quote you receive after scoping.
The almost-ready AI build covers the proven feature set. Custom trust policies, employer analytics products, or multi-market taxonomies add scoped estimate work.
Company taxonomies, language packs, and salary bucketing are configured per market. Adding markets means more configuration, never a rebuild.
Payment gateways, job feeds, and notification providers are wired during the build, and each integration is estimated individually.
Out of the box, moderation screening, outlier detection, and sentiment analysis are pre-tuned for review content. Training models on your historical content is an optional, separately scoped workstream.
Extend the Glassdoor-style build once the core trust loop is running.
Interview-process reviews with role-specific questions, the contribution type job seekers value most before applying.
Structured benefits data per employer with comparison views, the intelligence HR buyers purchase.
Response-rate and sentiment reporting for claimed employers, the dashboard that renews subscriptions.
Offer-comparison and negotiation-context features for members, deepening engagement around the salary corpus.
Native posting flow connecting review traffic to applications on the same codebase family, closing the two-sided loop.
Deploy the platform for industry-vertical operators under their own identity, with per-tenant moderation and claim configuration.
Community platforms live or die on trust engineering.
Anonymity, verification, and appeal flows are engineered into the data model, not patched on after your first legal complaint.
Company seeding, taxonomy, and employer claim workflows are built for the empty-launch problem every review site faces.
100% source-code transfer with no revenue share, refined across 9,000+ delivered projects.
Review traffic converts to job applications naturally. Pair this platform with our Indeed-style job board on the same codebase family.
Canonical deployments from our own portfolio. Metrics are reported from live platforms, not projections.
A high-volume two-sided platform proving content and fulfillment cores stay reliable at scale, from the same discipline.
A high-traffic consumer platform our team ships and operates, the standard every consumer engagement is measured against.
Tap a card to see how the platform defends its trust.
Contributions move through screened, approved, disputed, and removed states with automated pattern checks and a human queue, because one fabricated review can cost the platform its entire value proposition.
Submissions store decoupled from member identity and employers only ever see the content and metadata you allow, so anonymity is a design constraint rather than a policy promise.
Identities verify against employment records without exposure, keeping contributions honest and contributors safe at the same time.
Submitted salaries normalize into role, seniority, and location buckets with outlier suppression, so aggregations inform without exposing anyone.
Audit trails on every moderation decision demonstrate good-faith process, the record defamation law and regulators both ask for.
Community content attracts seekers, traffic attracts employers, and subscriptions fund moderation, so each side's behavior is the other's supply.
the process
You begin with a discovery call covering your market, content policy, and employer package pricing, followed by a written quote. Once you approve, you hand over your brand assets and we configure the platform: your identity across all three panels, your moderation rules, salary buckets, and packages. The almost-ready AI build goes live in 6 working days; a custom build takes 3 to 4 weeks, planned with you up front.
After launch, 60 days of included support and 12 months of updates cover the content-policy questions that surface with your first disputes. The first 90 days are a cold-start phase: seeding company records so early users review real employers, moderating actively to set the tone, and signing up the first claimed companies whose subscriptions fund the moderation. Platforms in this category live or die on trust in the content, so expect moderation discipline to matter more than growth tactics.
Open the web app, sign in with the printed demo credentials, or install the Android build — no signup, no sales call. What you see is what you launch.
Login: [email protected] | User_321 [email protected] | Employer_321
$ moxace launch --nowBook a free consultation and get your launch plan.
Share your idea
a quick call, no deck required
See the live demo
every screen, admin to user
Launch with source
full code, your brand, your servers
Moxace is an independent software development company. We are not affiliated with, sponsored by, or endorsed by Glassdoor.
The phrase “Glassdoor clone” is used descriptively. It is how the software industry refers to building a platform with similar functionality, and how buyers search for one.
The design and codebase are built entirely by our in-house team. Nothing is taken from the Glassdoor website, applications, or brand assets.
Glassdoor and all third-party names and marks remain the property of their respective owners, referenced here only to describe the category of software we build.
Read the full legal notice on our disclaimer page.