Spoken English practice and feedback studio

For

Language schools, corporate learning teams and independent coaches delivering spoken English programmes

Solves

Learners get little speaking practice and slow correction, while tutors cannot listen to every attempt or track progress consistently.

Delivers

Tutor-approved practice feedback and progress records

Built in

about 5 weeks of creation time, MVP in 6 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

Increase reviewed speaking attempts per learner without adding tutor hours.

1. Capture spoken attempts and return immediate pronunciation feedback.
2. Build personalised practice paths from level and goals.
3. Run interactive speaking exercises and prompts.
4. Simulate real-life dialogues for chosen contexts.
5. Track progress with reports over time.
6. Check grammar during speaking or writing.
7. Support practice in additional languages.
8. Provide instant translation of conversations.
9. Award points, badges and rewards.
10. Generate new exercises from conversation history.
11. Suggest writing style and tone for different audiences.
12. Offer contextual vocabulary suggestions.
13. Explain each suggested edit.
14. Estimate likely accent influences from a short sample.
15. Score closeness to a native-speaker model.
16. Give sound-by-sound pronunciation tips.
17. Let tutors set exercise difficulty.
18. Suggest phrases to keep conversations flowing.
19. Compare the reviewed result with the recorded baseline and value assumptions.
20. Capture corrections and named-owner approval before consequential use.
21. Export versioned tutor-approved practice feedback and progress records with source references and unresolved questions.

Everything these tools do, in one app

• Real-time pronunciation feedback Provides immediate feedback on pronunciation errors to help users correct mistakes as they speak.Found in elsaspeak, Kippy AI, Play It, Say It
• Personalized learning paths Tailors lessons and exercises to the user's current proficiency level and goals.Found in elsaspeak, Vocalo
• Interactive speaking exercises Offers interactive lessons and prompts to practice speaking in a structured way.Found in elsaspeak, Play It, Say It
• Conversation simulations Simulates real-life dialogues to practice speaking in various contexts.Found in elsaspeak, Vocalo, Kippy AI
• Progress tracking Monitors improvement over time with detailed reports and insights.Found in Vocalo, Kippy AI, Play It, Say It
• Grammar feedback Checks and provides feedback on grammar usage during speaking or writing.Found in Kippy AI, Fluently
• Multi-language support Allows practice in multiple languages beyond English.Found in Kippy AI, Play It, Say It
• Instant translation Provides real-time translation of conversations to aid understanding.Found in Vocalo, Kippy AI
• Gamified rewards Motivates learning through points, badges, and rewards.Found in Vocalo
• Dynamic exercise generation Creates exercises based on conversation history and progress to target areas needing improvement.Found in Vocalo
• Writing style and tone suggestions Offers suggestions to adjust writing style and tone for different audiences.Found in Fluently
• Vocabulary enhancement Provides contextual vocabulary suggestions to improve word choice and sentence flow.Found in Fluently
• Detailed edit explanations Explains suggested edits to help users learn and improve.Found in Fluently
• Accent origin breakdown Estimates the likely accent influences based on a short speech sample.Found in Fluently Accent Guru
• Native Meter score Scores how close the user's English sounds to a native speaker.Found in Fluently Accent Guru
• Sound-by-sound tips Provides specific pronunciation tips for individual sounds.Found in Fluently Accent Guru
• Customizable difficulty levels Allows users to adjust the difficulty of exercises to suit their skill level.Found in Play It, Say It
• Guided conversation suggestions Offers suggestions to help keep conversations flowing.Found in Kippy AI

What goes in, what comes out

The workflow

1. In
   Start with

   Learner speech samples, curriculum goals and tutor rubrics

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect learner speech samples

4. 3

   Curriculum goals and tutor rubrics

5. 4

   Then follow this sequence: 1

6. Out
   Finish with

   Tutor-approved practice feedback and progress records

AI does the heavy lifting, people stay in charge

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

What your team sees

Primary screens: Programme and rubric setup, Learner practice session, Tutor review and progress. Use a cohort list for programmes, a large central practice canvas with recording and playback, and a right-hand panel for prompts, feedback and tutor comments. Let tutors compare attempts side by side. Display draft, changes requested and approved states. Provide a learner practice link with feedback anchored to the relevant utterance. Make the task-specific outcome tutor-approved practice feedback and progress records visible beside its evidence, review state and value baseline.

Accounts and administration

Programme ownership, learner records, tutor comments, approval states, practice allowances, session limits, download history and a consent record for recorded speech. 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 learner records, authorised speech samples and permitted curriculum sources. Cloud audio storage, learning-management-system import/export and reporting destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorised file exchange. Validate current provider access, usage rights and schema behaviour 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

   6 days

   One buyer segment, one recurring use case; first modules: capture spoken attempts and return immediate pronunciation feedback; build personalised practice paths from level and goals. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   7 days

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

4. 4

   Full product

   2 weeks

   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 language schools, corporate learning teams and independent coaches delivering spoken English programmes use it to solve "learners get little speaking practice and slow correction, while tutors cannot listen to every attempt or track progress consistently"?
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: Reviewed speaking attempts per tutor hour and learner improvement on agreed speaking criteria.
4. Measure, then decide. Track reviewed speaking attempts per tutor hour and learner improvement on agreed speaking criteria; 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 defined curriculum level and a fixed rubric; final assessment and progression decisions remain with the tutor. Implement one approved input format, a bounded representative learner set and the first two task modules: capture spoken attempts and return immediate pronunciation feedback; build personalised practice paths from level and goals. Support the remaining modules with operator review: interactive exercises, dialogue simulations, progress tracking, grammar feedback, translation, rewards, generated exercises, writing suggestions, vocabulary help, edit explanations, accent estimates, native-meter scoring, sound tips, difficulty settings and conversation prompts. 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 languages and learner volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around tutor-approved practice feedback and progress records. Retain the explicit scope boundary: One defined curriculum level and a fixed rubric; final assessment and progression decisions remain with the tutor.

What the build depends on. Audio upload and playback, asynchronous scoring jobs, editable version history, reviewer access and tested export formats. High-fidelity assessment requires specialist language QA. Obtain representative authorised cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One defined curriculum level and a fixed rubric; final assessment and progression decisions remain with the tutor.

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 learner cohort. Offer a monthly practice allowance after repeat demand. Quote specialist assessment or multi-language expansion separately. These are test prices, not market benchmarks. Package the initial sale as one bounded tutor-approved practice feedback and progress records set. Recurring fees must specify learner 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

Increase reviewed speaking attempts per learner without adding tutor hours. Demonstrate a concrete tutor-approved practice feedback and progress records set using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Language schools, corporate learning teams and independent coaches professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample tutor-approved practice feedback and progress records set from a small authorised input set, with a transparent calculation of reviewed speaking attempts per tutor hour and learner improvement on agreed speaking criteria and no promised savings.

The first 30 days

1. Week 1: interview five language schools, corporate learning teams and independent coaches delivering spoken English programmes and inspect a recent example of learners get little speaking practice and slow correction, while tutors cannot listen to every attempt or track progress consistently.
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 reviewed speaking attempts per tutor hour and learner improvement on agreed speaking criteria, 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: Reviewed speaking attempts per tutor hour and learner improvement on agreed speaking criteria. 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

Reviewed speaking attempts per tutor hour and learner improvement on agreed speaking criteria; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs tutor-approved practice feedback and progress records. Retain permissioned settings and reviewed examples, report realised 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 rubrics, curriculum mappings and reviewed learner examples, together with reliable delivery for a narrow education niche. Build a permissioned library of representative learner cases, tutor corrections and verified operating constraints for language schools, corporate learning teams and independent coaches delivering spoken English programmes. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

elsaspeak, Vocalo, Fluently, Kippy AI, Play It, Say It and Fluently Accent Guru, plus tutors, classroom practice and generic recording tools. Compare this product with the buyer's present method on reviewed speaking attempts per tutor hour and learner improvement on agreed speaking criteria. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Speech processing, storage, reviewer hours, learner revision rounds and licensed curriculum assets. Additional initial validation requires representative authorised sample preparation, buyer interviews, buyer-side evaluation and bounded validation of tutor-approved practice feedback and progress records. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve learner voice, source attribution, consent for recorded speech and usage permissions. Tutors approve substantive assessment and progression decisions. One defined curriculum level and a fixed rubric; final assessment and progression decisions remain with the tutor. Keep all consequential actions under authorised human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.