Step-by-step tutoring and homework practice platform

For

Schools, tutoring centers and training providers supporting students in math and science

Solves

Students get stuck on homework without guided steps, while teachers cannot review every attempt or see where understanding breaks down.

Delivers

Reviewed step-by-step explanations, practice sets and progress reports

Built in

about 4 weeks of creation time, MVP in 4 days

Investment

$13,500 for the MVP, $46,000 for the full product

Run it

Inside your business, or as part of your offer to clients

Give students guided step-by-step help and give teachers evidence of where each learner is stuck.

1. Accept typed, photographed or spoken problems.
2. Break each problem into clear steps.
3. Ask guiding questions instead of giving answers outright.
4. Show visual and graph-based explanations.
5. Provide instant feedback on each attempt.
6. Adapt difficulty to the learner's responses.
7. Generate custom quizzes per topic.
8. Offer short video or animated explanations.
9. Track progress on a knowledge map.
10. Flag recurring mistakes for the teacher.
11. Support on-screen annotation and sketching.
12. Allow teacher review and correction of explanations.
13. Compare the reviewed result with the recorded baseline and value assumptions.
14. Capture corrections and named-owner approval before consequential use.
15. Export a versioned reviewed step-by-step explanations, practice sets and progress reports with source references and unresolved questions.

Everything these tools do, in one app

• Step-by-step problem solving Breaks down complex problems into clear, manageable steps to guide users to the solution.Found in Bytelearn, MathGPT, StudyX and 3 more
• Personalized learning Adapts tutoring and content to individual learning paces, styles, and needs.Found in Bytelearn, MathGPT, MathGPTPro and 2 more
• Real-time feedback Provides instant feedback as users work through problems to help correct mistakes and deepen understanding.Found in Bytelearn, MathGPTPro
• Interactive tutoring Offers real-time, conversational tutoring sessions that emulate one-on-one learning.Found in MathGPTPro, ChatGPT study mode
• Socratic questioning Uses questioning techniques to encourage critical thinking and deeper understanding.Found in MathGPTPro
• Visual explanations Provides visual interpretations and aids to make concepts more intuitive.Found in Socratic, Koji by Brilliant
• Image recognition input Allows users to submit problems by taking or uploading a picture for analysis.Found in StudyX, Sizzle AI
• Voice and text interaction Supports both voice and text input for accessible interaction in multiple languages.Found in Koji by Brilliant, Socratic
• Custom quizzes Generates personalized quizzes tailored to specific topics to reinforce learning.Found in MathGPT, Bytelearn
• Graphing and visualization tools Offers graphing capabilities to illustrate mathematical problems and concepts.Found in MathGPT
• Video explanations Provides on-demand video explanations with animations, diagrams, and voiceovers.Found in MathGPT
• Progress tracking Monitors student progress through a knowledge graph and heatmap to tailor tasks and rewards.Found in MathGPTPro
• Teacher support Automates homework assessment and provides insights into student mistakes for educators.Found in MathGPTPro
• On-screen annotation Enables pointing, sketching, and annotation to highlight steps and parts of problems.Found in Koji by Brilliant
• Adaptive coaching Adjusts guidance by breaking problems into steps or increasing challenge based on learner responses.Found in Koji by Brilliant
• Community Q&A Provides access to millions of community-driven questions and answers for additional support.Found in StudyX
• 24/7 expert support Offers round-the-clock assistance from subject experts for urgent homework help.Found in StudyX
• Multi-platform access Allows users to access the tool on laptops, smartphones, and other devices.Found in StudyX

What goes in, what comes out

The workflow

1. In
   Start with

   Authorized curriculum material, student work and teacher constraints

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect authorized curriculum material

4. 3

   Student work and teacher constraints

5. 4

   Then follow this sequence: 1

6. Out
   Finish with

   Reviewed step-by-step explanations, practice sets and progress reports

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed subject set and grade band; final grading and curriculum decisions remain with teachers. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Subject and curriculum setup, Student practice workspace, Teacher review and reports. Use a class list for students, a large central problem canvas with step-by-step panels, and a right-hand panel for hints, sources and teacher comments. Let students compare their attempt with the guided steps. Display draft, needs review and approved states. Provide a teacher dashboard with per-student progress and flagged mistakes. Make the task-specific outcome reviewed step-by-step explanations, practice sets and progress reports visible beside its evidence, review state and value baseline.

Accounts and administration

Class ownership, student records, teacher comments, approval states, usage allowances, session limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

School-owned curriculum material, authorized student work and permitted practice sources. Cloud file storage, learning management system import/export and reporting destinations. Start with file exchange and validate destination specifications before promising direct gradebook sync. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   4 days

   One buyer segment, one recurring use case; first modules: accept typed, photographed or spoken problems; break each problem into clear steps. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   5 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   10 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will schools, tutoring centers and training providers supporting students in math and science use it to solve "students get stuck on homework without guided steps, while teachers cannot review every attempt or see where understanding breaks down"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Problems completed with understanding and teacher review time per student.
4. Measure, then decide. Track problems completed with understanding and teacher review time per student; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One fixed subject set and grade band; final grading and curriculum decisions remain with teachers. Implement one approved input format, a bounded representative case set and the first two task modules: accept typed, photographed or spoken problems; break each problem into clear steps. Support the third module with operator review: ask guiding questions instead of giving answers outright. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewed step-by-step explanations, practice sets and progress reports. Retain the explicit scope boundary: One fixed subject set and grade band; final grading and curriculum decisions remain with teachers.

What the build depends on. Student work upload and preview, asynchronous generation jobs, editable version history, teacher access and tested export formats. High-fidelity tutoring requires subject-qualified review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed subject set and grade band; final grading and curriculum decisions remain with teachers.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined class package. Offer a monthly per-seat allowance after repeat demand. Quote complex multi-subject or certification work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed step-by-step explanations, practice sets and progress reports. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Give students guided step-by-step help and give teachers evidence of where each learner is stuck. Demonstrate a concrete reviewed step-by-step explanations, practice sets and progress reports using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Schools, tutoring centers and training providers supporting students in math and science professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed step-by-step explanations, practice sets and progress reports from a small authorized input set, with a transparent calculation of problems completed with understanding and teacher review time per student and no promised savings.

The first 30 days

1. Week 1: interview five schools, tutoring centers and training providers supporting students in math and science and inspect a recent example of students get stuck on homework without guided steps, while teachers cannot review every attempt or see where understanding breaks down.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure problems completed with understanding and teacher review time per student, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Problems completed with understanding and teacher review time per student. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Problems completed with understanding and teacher review time per student; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewed step-by-step explanations, practice sets and progress reports. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved explanations, curriculum constraints and review examples, together with reliable delivery for a narrow education niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for schools, tutoring centers and training providers supporting students in math and science. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Bytelearn, MathGPT, MathGPTPro, Koji by Brilliant, Socratic, StudyX, Sizzle AI and ChatGPT study mode. Compare this product with the buyer's present method on problems completed with understanding and teacher review time per student. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model calls, image and voice processing, storage, reviewer hours, teacher revision rounds and licensed curriculum assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed step-by-step explanations, practice sets and progress reports. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve student privacy, source attribution, curriculum accuracy and usage permissions. Teachers approve substantive explanations and grading scope. One fixed subject set and grade band; final grading and curriculum decisions remain with teachers. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.