Animated lesson libraries
Concept videos organized by grade and syllabus, with resume points and offline downloads.
AI-Built Byju's Clone
An AI-first build of every learning mechanic: an adaptive practice engine driven by per-student mastery estimates, learning-gap prediction that guides mentors, and retention scoring that protects renewals. Four 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 facts behind every build.
overview
A Byju's-style learning app is a full edtech platform: animated lesson libraries, adaptive practice, scheduled live classes, assigned mentors, and parent visibility, delivered under your brand.
Its purpose is to sell structured learning outcomes rather than raw content. Parents and students subscribe because mastery tracking, mentor accountability, and live teaching promise progress; the operator owns the subscription, the data, and the pedagogy stack.
The build covers the student app with lessons and quizzes, teacher tools for live classes, a mentor console for accountability workflows, and combined admin and parent panels for operations and family reporting.
Digital learning settled into a permanent layer of education after its rapid adoption in recent years, and demand concentrates on platforms that can demonstrate progress. The structural insight the category has matured into is simple: outcomes and accountability, not content volume, are what renew subscriptions.
The summary layer above the role panels.
Concept videos organized by grade and syllabus, with resume points and offline downloads.
Quiz difficulty adjusts to per-student mastery estimates, surfacing weak areas instead of hiding them in averages.
Scheduling, attendance, whiteboard, and recordings run inside the platform, keeping teaching on your brand.
Mentors get rosters, learning-gap dashboards, and check-in scheduling, making accountability systematic.
Progress reports generate from the same mastery data students see, keeping families engaged in renewal decisions.
Habit mechanics keep students practicing between live sessions.
Course and batch pricing, mentor allocation, and renewal offers all configure from the admin panel.
What these buyers share: a curriculum or teaching approach their market trusts, and the intent to own the subscription relationship.
Build a test-prep or K12 business on a platform where mastery data, not marketing claims, renews the subscription.
Extend your classrooms to an app without losing the mentor accountability that makes your teaching work.
Turn strong teaching material into structured courses, with adaptive practice proving the outcomes parents pay for.
Run every franchise branch on one platform, with batch quality and mentor performance measured centrally.
Adapt the same mastery-and-mentor architecture for workforce learning, with progress reporting your stakeholders can audit.
Every panel below ships in every build.
Learning that holds attention across a full syllabus.
Run scheduled classes without third-party apps.
The human accountability layer behind outcomes.
Business operations plus family visibility.
Beyond course administration: the operational systems that keep a learning platform governable at scale.
Lesson libraries, quizzes, and test series publish through a review workflow with syllabus mapping per grade and market, so content investment follows the mastery-lift evidence your analytics produce.
Assignment rules match mentor rosters to capacity, check-in completion and escalation flags report per mentor, and quality is measured centrally, so accountability scales beyond a handful of star teachers.
Assessment attempt controls, plagiarism and pattern checks on graded work, moderation of discussion spaces, and strict student-data access controls protect the platform's credibility with parents and schools.
Renewal-risk cohorts, batch economics, mentor program margins, and revenue per grade report into one dashboard, so the outcome story your parent reports tell is priced and staffed correctly.
The learning journey from enrollment to the parent's report.
The student subscribes to a grade and subject plan, and the app builds a study path across the syllabus map.
Concept videos play in sequence with resume points and offline downloads, so learning survives a commute or a weak connection.
Quizzes adjust difficulty to the student's mastery estimates, and weak areas flag themselves for review rather than hiding in an average score.
Scheduled in-app classes add teaching, whiteboard, attendance, and a question queue, with recordings published for anyone who missed the session.
A mentor assigned by grade or batch reviews the learning-gap dashboard, schedules check-ins, and adjusts the study plan.
The parent panel mirrors lesson completion, test scores, and mentor notes, generated from the same mastery data the student app uses.
Five model-driven systems working the same learning stream. Each ships pre-tuned for edtech and sharpens as your data compounds.
Updates a per-student mastery estimate on every quiz answer and adjusts difficulty, so practice targets the frontier of what the student almost knows.
Quiz responses, time-on-task, concept prerequisites
Practice that measurably moves mastery instead of averaging it
Projects which concepts a student will fail next, so mentors intervene before the test does.
Mastery trajectories, prerequisite graphs, error patterns
Mentors spend their hours on the students who need them most
Flags subscriptions whose engagement is slipping before the parent decides not to renew.
Practice frequency, class attendance, parent-report engagement
Renewal conversations happen while the outcome story is still strong
Ranks which lessons and explanations actually move mastery, so content investment follows evidence.
Completion rates, mastery lift per lesson, rewatch patterns
Course libraries improve on data instead of anecdote
Sequences lessons, practice, and revision per student from their mastery map and syllabus calendar.
Mastery map, exam dates, study habits
Every student follows a plan that fits their gaps
The modules that turn a lesson library into a full learning product, each toggleable and configurable per grade.
Mock exams and adaptive test series that prepare students for real assessments, with difficulty tuned to mastery estimates and results feeding the same learning-gap dashboards mentors see.
Interactive simulations for science and applied subjects, giving hands-on understanding of concepts video alone cannot teach, with completion tracked in the mastery store.
Augmented-reality views of complex concepts, from geometry to anatomy, that raise engagement and retention where flat video struggles.
Streaks, achievement badges, and daily goals that keep students practicing between live sessions, wired to the same engagement data renewal scoring reads.
Course-linked certificates issued on demonstrated completion, giving students portable evidence of progress and giving parents a tangible outcome artifact.
Doubt-clearing chat with mentors plus structured discussion spaces per course, so questions surface early instead of becoming silent drop-offs.
revenue model
Mastery data is the platform's spine. Every quiz answer updates a per-student mastery estimate, and that single data set drives adaptive difficulty, mentor dashboards, and parent reports, so all three surfaces describe the same learner consistently instead of maintaining separate scores.
The mentor is a systematic layer, not a support extra. Assignment rules in the admin panel match mentor capacity to roster size, the console surfaces learning gaps and escalation flags per student, and check-ins are scheduled from the same view. Accountability becomes a workflow rather than a personality trait of one good teacher.
Live teaching stays inside the product. Scheduling, capacity, attendance, and recordings run through the platform's own classroom, which keeps the data, the brand, and the subscription value in one place, and lets the admin panel measure batch quality the same way it measures content performance.
revenue model
Digital learning has settled into a permanent layer of education, and the demand that survives is concentrated where progress is demonstrable. Parents renew subscriptions when mastery data, mentor accountability, and live teaching show a child advancing; content volume alone stopped being a selling point the moment every platform had a large library.
That is why the outcomes layer is where the economics live. Adaptive practice and test series prepare students for assessments that measurably matter, mentor programs turn accountability into a product feature, and parent reports convert learning data into the renewal argument. Immersive formats such as virtual labs and AR visualizations raise engagement where concepts are hard to grasp from video alone. The revenue lines below quantify where each of these earns.
Course subscriptions by grade and subject duration, with renewal pricing configured in the admin panel.
Live class batches sold as premium add-ons to self-paced video access.
One-on-one mentor programs billed monthly, with assignment rules that match mentor capacity to roster size.
Test series and exam-prep packages for competitive segments.
Every plan, batch price, and mentor allocation is admin-configurable, so you can tune offers per grade and market without a code release.
Six monetization lines across the learning platform, quantified against published industry benchmarks. Every rate is configurable in your admin panel; 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 |
|---|---|---|---|---|
| Course subscriptions | A recurring or term-based fee per grade and subject bundle | K12 subscription apps commonly price $10 to $30 per month per student, with annual plans discounted | Renewal, not acquisition. Mastery data and parent reports are what make the second year happen | |
| Live class batches | A premium fee for scheduled batches with real teachers, sold on top of self-paced access | Batch pricing varies widely by market; premium live tiers typically double the base subscription | Teacher capacity. Scheduling, attendance, and batch quality tooling decide how much live supply you can sell | |
| Mentor programs | A monthly fee for one-on-one mentor accountability | Commonly $15 to $50 per month depending on depth and market | Roster economics. Assignment rules matching mentor capacity to student load set the margin on this line | |
| Test series and exam prep | One-time or seasonal packages for competitive-exam preparation | Test-prep packages commonly $20 to $100 per exam cycle | Outcome credibility. Packages sell where past results are demonstrable, which the assessment analytics provide | |
| Certification programs | Course-linked certificates issued on completion, sold as standalone programs or bundled | Pricing varies by subject; certificates monetize completion evidence | Employer demand. Certificates earn what the market pays for verifiable skill signals | |
| Institutional licensing | Per-seat or per-campus licensing to schools and institutes running your platform as their LMS | Contract-specific per institution size and module scope | Procurement cycles. Institutional deals are slower but anchor revenue that consumer churn never touches |
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 recurring course billing with parent-friendly checkout.
The adaptive mastery engine, learning-gap prediction, and renewal scoring arrive configured for edtech, 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.
Where learning platforms succeed or stall technically.
Quiz difficulty adjusts to per-student mastery estimates, and the same data drives mentor dashboards, so intervention is targeted rather than guesswork.
Encrypted lesson video with DRM, offline downloads, and resume points, tuned for school-network and low-bandwidth conditions.
Scheduled in-app classes with attendance, recordings, and capacity limits, so live teaching stays inside your product instead of leaking to third-party tools.
React Native student and mentor apps, Next.js web panels, and Node.js services with the mastery store shared across every surface.
Payment gateways, video CDN and DRM providers, SMS and push notification services, and analytics platforms ship as configured integrations, so the platform plugs into the tools your operations already run on.
Role-based access, student data protection with strict access controls, append-only audit logs, and encrypted traffic and secrets come standard, so parent and school data 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.
Grades, subjects, batch model, and mentor program locked with a written scope, and your identity applied across all four panels.
Payment gateways, live classroom, video DRM, and plan structures configured and tested against your live accounts.
Launch lesson libraries and quizzes imported with the first live class schedule, then a full pilot: enroll, lesson, quiz, class, mentor check-in.
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 mastery 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 |
| Curriculum fit | Your launch grades and subjects configured on the proven mastery core | Curriculum mapping and pedagogy tools built to your teaching IP |
| 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 adaptive practice, the live classroom, and the mentor console 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 curriculum tooling or assessment integrations add scoped estimate work.
Syllabus maps, language packs, and pricing tiers are configured per grade and market. Adding grades means more configuration, never a rebuild.
Payment gateways, video and DRM providers, and notification services are wired during the build, and each integration is estimated individually.
Out of the box, the mastery engine, gap prediction, and renewal scoring are pre-tuned for edtech. Training models on your historical learning data is an optional, separately scoped workstream.
The extensions education operators most often add once the core learning loop is proven, each scoped as its own workstream.
Assignment and homework grading automation beyond quizzes, including rubric-based scoring, saving educator hours at batch scale.
Connections to content providers, assessment platforms, and school information systems so the platform plugs into the ecosystem your market already uses.
Aggressive offline caching and low-bitrate delivery tiers for markets where connectivity is the adoption constraint.
Per-campus branded instances for schools and institutes, licensed from the same codebase with separate branding and data isolation.
Ready-made speed with custom-build discipline.
The per-student mastery store drives practice, mentoring, and parent reports from one data set, not three disconnected scores.
A ready-made launch costs a fraction of a ground-up build, with a fixed written quote before work starts.
One hundred percent of the source code transfers to you. No per-student royalties, no black-box dependencies.
Education is one of our served industries. For the wider vertical, see our education and edtech industry practice.
Canonical deployments from our own portfolio. Metrics are reported from live platforms, not projections.
A high-traffic consumer platform our team ships and operates at national-carrier scale, the same engagement bar every consumer platform is held to.
A high-concurrency digital platform our engineering system ships and operates at 99.9% uptime, the same reliability bar every learning platform is held to.
A high-volume consumer platform proving notification and engagement loops hold at scale, from the same discipline.
A learning platform holds children's data and parents' payment details. The controls are built in, and stated plainly.
Strict role-based access limits who sees student records, append-only audit logs record every access, and retention policies are privacy-aware, because data about minors is the most sensitive data a platform can hold.
Parent reports generate from the same mastery store students experience, so the family view can never drift from the actual learning record.
Attempt controls, timing rules, and integrity checks on graded work keep test results meaningful, which is what makes outcome claims defensible.
Recurring billing with clear invoices, refunds routed by original payment method, and reconciliation views, so subscription finance closes from platform data.
Doubt-clearing and course discussions run through moderation queues and reporting tools, keeping the community safe for the age group it serves.
the process
Discovery maps grades, subjects, batch model, and mentor program, ending in a written scope and fixed quote. Once you approve, you hand over your brand assets and we configure the platform: your identity across all four panels, your plans, batches, and mentor assignment rules. The almost-ready AI build goes live in 6 working days; a custom build takes 3 to 4 weeks, planned with you up front.
Launch is not the finish line. You get 60 days of included support and 12 months of updates covering bug fixes and OS compatibility releases. The first 90 days are outcome proof: expect to watch mastery and completion data, adjust batch schedules, and use parent reports as the renewal argument they are designed to be. The software measures the learning; your teaching quality is what the data will show.
$ moxace launch --nowBook a free consultation and get a written scope and quote.
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 Byju's.
The phrase “Byju's 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 Byju's website, applications, or brand assets.
Byju's 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.