Source-based reading and transcription workspace

For

Writers, editors and researchers who work from written text or audio recordings

Solves

Reading, transcribing and repurposing source material is split across several subscriptions, so text and audio work never stays in one owned workflow.

Delivers

Editor-approved spoken or written text linked to its source

Built in

about 5 weeks of creation time, MVP in 5 days

Investment

$14,500 for the MVP, $49,500 for the full product

Run it

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

Reduce the number of tools and manual steps needed to turn written text or audio into spoken or written text you can listen to or read.

1. Convert written text into spoken audio.
2. Transcribe audio recordings into editable text.
3. Support content in multiple languages.
4. Accept audio files in formats such as MP3 and WAV.
5. Produce real-time transcription as audio plays.
6. Let editors refine and correct transcribed text.
7. Add timestamps for navigation to specific points.
8. Connect with productivity tools and platforms.
9. Read the main body text from articles, blog posts, newsletters, documentation and long threads.
10. Highlight the current passage and mark the spoken word during playback.
11. Stream audio on play or pre-generate the full article with a scrub bar.
12. Export WAV files with embedded word timings that preserve read-along on re-open.
13. Store API keys and settings locally and send page text only after play is pressed.
14. Work with any voice in the user's voice library, including cloned and custom-designed voices.
15. Extract concise overviews from longer texts.
16. Elaborate on short notes or summaries for additional context.
17. Generate content suitable for social media posting.
18. Create or refine lyrical content.
19. Build personalized shortcuts using prompts and inputs.
20. Produce natural-sounding voice output.
21. Process text locally for privacy and offline use.
22. Convert an entire web page to speech with one click.
23. Avoid uploading content to external servers.
24. Run as a browser extension.
25. Compare the reviewed result with the recorded baseline and value assumptions.
26. Capture corrections and named-owner approval before consequential use.
27. Export a versioned editor-approved spoken or written text linked to its source with source references and unresolved questions.

Everything these tools do, in one app

• Text-to-speech conversion Turns written text into spoken audio you can listen to.Found in Lisen, Quickie, Parrot TTS
• Speech-to-text transcription Converts audio recordings into accurate, editable written text.Found in Audeus
• Multi-language support Works with content in various languages.Found in Audeus
• Multiple audio formats Accepts audio files in formats such as MP3 and WAV.Found in Audeus
• Real-time transcription Produces transcriptions with minimal delay as audio plays.Found in Audeus
• Editable transcripts Lets you refine and correct the transcribed text.Found in Audeus
• Timestamped navigation Adds timestamps to transcripts so you can jump to specific points.Found in Audeus
• Productivity tool integrations Connects with popular productivity tools and platforms.Found in Audeus
• Web page reading Reads the main body text from articles, blog posts, newsletters, documentation, and long threads.Found in Lisen, Parrot TTS
• Visual read-along Highlights the current passage and marks the spoken word on the page as audio plays.Found in Lisen
• Instant streaming or pre-generation Streams audio immediately on play or generates the full article ahead of time with a scrub bar.Found in Lisen
• WAV export with word timings Exports an article as a WAV file with embedded word timings that preserve the read-along feature on re-open.Found in Lisen
• Local key storage Stores the API key and settings locally in the browser and sends page text only after you press play.Found in Lisen
• Custom voice library Works with any voice in your voice library, including cloned and custom-designed voices.Found in Lisen
• Summarization Extracts concise overviews from longer texts.Found in Quickie
• Text expansion Elaborates on short notes or summaries for additional context.Found in Quickie
• Social media content generation Generates content suitable for social media posting.Found in Quickie
• Lyrics generation Creates or refines lyrical content.Found in Quickie
• Custom shortcuts Builds personalized shortcuts using prompts and inputs to automate repetitive tasks.Found in Quickie
• Natural-sounding voices Produces human-like voice output that avoids robotic speech patterns.Found in Parrot TTS
• Offline processing Processes text locally to ensure privacy and eliminate reliance on internet connectivity.Found in Parrot TTS
• One-click full page parsing Converts an entire web page to speech with a single click.Found in Parrot TTS
• Privacy-first design Avoids uploading content to external servers.Found in Parrot TTS
• Chrome extension Integrates with web browsing as a Chrome extension.Found in Lisen, Quickie, Parrot TTS

What goes in, what comes out

The workflow

1. In
   Start with

   Licensed source text, audio recordings, voice settings and editorial constraints

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect licensed source text

4. 3

   Audio recordings

5. 4

   Voice settings and editorial constraints

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Editor-approved spoken or written text linked to its source

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 arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Final editorial checks and publication decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Source intake and settings, Editable production preview, Client proof and delivery. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for sources, constraints and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant passage or timestamp. Make the task-specific outcome editor-approved spoken or written text linked to its source visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, asset versions, client comments, approval states, usage allowances, revision 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

Author-owned manuscripts, authorized recordings and permitted research sources. Cloud asset storage, document import/export and publishing destinations. Start with file exchange and validate destination specifications before promising direct publishing. 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

   5 days

   One buyer segment, one recurring use case; first modules: convert written text into spoken audio; transcribe audio recordings into editable text. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 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 writers, editors and researchers who work from written text or audio recordings use it to solve "reading, transcribing and repurposing source material is split across several subscriptions, so text and audio work never stays in one owned workflow"?
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: Accepted outputs per editorial hour and corrections after approval.
4. Measure, then decide. Track accepted outputs per editorial hour and corrections after approval; 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 approved input format, a bounded representative case set and the first two task modules: convert written text into spoken audio; transcribe audio recordings into editable text. Support the remaining modules with operator review. 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 editor-approved spoken or written text linked to its source. Retain the explicit scope boundary: final editorial checks and publication decisions remain human.

What the build depends on. Asset upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity production requires specialist editorial QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: final editorial checks and publication decisions remain human.

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 source package. Offer a monthly production allowance after repeat demand. Quote complex audio, video or specialist editorial work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded editor-approved spoken or written text linked to its source. 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

Reduce the number of tools and manual steps needed to turn written text or audio into spoken or written text you can listen to or read. Demonstrate a concrete editor-approved spoken or written text linked to its source using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Writers, editors and researchers professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample editor-approved spoken or written text linked to its source from a small authorized input set, with a transparent calculation of accepted outputs per editorial hour and corrections after approval and no promised savings.

The first 30 days

1. Week 1: interview five writers, editors and researchers who work from written text or audio recordings and inspect a recent example of reading, transcribing and repurposing source material being split across several subscriptions.
2. Week 2: prepare a consented or synthetic demonstration of the task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure accepted outputs per editorial hour and corrections after approval, 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: Accepted outputs per editorial hour and corrections after approval. 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

Accepted outputs per editorial hour and corrections after approval; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs editor-approved spoken or written text linked to its source. 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 styles, production constraints and review examples, together with reliable delivery for a narrow editorial niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for writers, editors and researchers who work from written text or audio recordings. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Audeus, Lisen, Quickie and Parrot TTS are used today as separate rented subscriptions. Compare this product with the buyer's present method on accepted outputs per editorial hour and corrections after approval. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, audio processing, storage, reviewer hours, client revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of editor-approved spoken or written text linked to its source. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve author voice, source attribution, quotation accuracy and usage permissions. Authors approve substantive changes and publication scope. Final editorial checks and publication decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.