Source-based writing and editorial delivery workspace

For

Writers, editors and content teams producing source-based articles, briefs and scripts

Solves

Writing, editing, research and delivery live in separate tools, so drafts, prompts, revisions and approvals are scattered and hard to trace.

Delivers

Editor-approved publishable drafts linked to their sources

Built in

about 5 weeks of creation time, MVP in 5 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

Reduce tool switching and revision cycles while keeping the writer's voice and source traceability.

1. Ingest and index licensed source material.
2. Suggest context-aware completions in the writer's style.
3. Generate draft content for defined formats.
4. Store and reuse custom prompts.
5. Answer questions inside the document.
6. Summarize long sources into main points.
7. Rewrite passages for clarity and tone.
8. Draft email replies from short prompts.
9. Apply a magic editor pass for clarity and style.
10. Build speeches from outlines, quotes and topics.
11. Support academic writing with citation checks.
12. Track progress and goals in an analytics dashboard.
13. Run focus sessions with a Pomodoro timer.
14. Browse a prompt library for starting points.
15. Toggle visibility of AI-generated text.
16. Track revisions and compare versions.
17. Support live collaboration and read-only publishing.
18. Compare the reviewed result with the recorded baseline and value assumptions.
19. Capture corrections and named-owner approval before consequential use.
20. Export a versioned editor-approved publishable draft linked to its sources with source references and unresolved questions.

Everything these tools do, in one app

• AI writing assistance Provides intelligent suggestions and completions to help users write text.Found in HyperWrite, Prose Fusion, Lex
• Context-aware suggestions Offers suggestions that adapt to the context and writing style.Found in HyperWrite, Prose Fusion, Lex
• Content generation Generates original content on various topics and formats.Found in HyperWrite, Lex
• Custom prompt library Allows users to create and access personalized AI prompts.Found in Prose Fusion, Lex
• Chat assistant Provides real-time writing support, brainstorming, and feedback within the document.Found in Prose Fusion
• Ask questions Lets users ask questions and receive instant answers without leaving the document.Found in Lex
• Summarizer Condenses articles and texts into main points.Found in HyperWrite
• Rewrite content Reframes existing text to improve clarity and style while maintaining meaning.Found in HyperWrite
• Email responder Generates well-crafted email replies based on rough ideas or short prompts.Found in HyperWrite
• Magic editor Improves clarity, tone, and style in documents and messages.Found in HyperWrite
• Speech writer Creates speeches using outlines, quotes, and topics.Found in HyperWrite
• Scholar AI Provides academic writing assistance.Found in HyperWrite
• Analytics dashboard Tracks writing progress and productivity with detailed metrics and goal tracking.Found in Prose Fusion
• Pomodoro timer Promotes focused work sessions and time management.Found in Prose Fusion
• Prompt marketplace Offers a marketplace for prompts to inspire creativity.Found in Prose Fusion
• Show AI hidden text Toggles visibility to distinguish between original and AI-generated content.Found in Lex
• Revision control Enables efficient tracking of changes to refine drafts.Found in Lex
• Collaboration tools Includes live collaboration, mobile web sharing, and read-only publishing.Found in Lex

What goes in, what comes out

The workflow

1. In
   Start with

   Licensed source material, style guides, editorial constraints and draft text

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect licensed source material

4. 3

   Style guides

5. 4

   Editorial constraints and draft text

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Editor-approved publishable drafts linked to their sources

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. One fixed style guide and licensed source set; final fact-checking and editorial judgment 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 brief, Editable writing canvas, Editorial review and delivery. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for sources, prompts, 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. Make the task-specific outcome editor-approved publishable drafts linked to their sources visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, source 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 interviews and permitted research sources. Cloud document storage, style-guide 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: ingest and index licensed source material; suggest context-aware completions in the writer's style. 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 content teams producing source-based articles, briefs and scripts use it to solve "writing, editing, research and delivery live in separate tools, so drafts, prompts, revisions and approvals are scattered and hard to trace"?
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 drafts per editorial hour and corrections after editorial approval.
4. Measure, then decide. Track accepted drafts per editorial hour and corrections after editorial 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 fixed style guide and licensed source set; final fact-checking and editorial judgment remain human. Implement one approved input format, a bounded representative case set and the first two task modules: ingest and index licensed source material; suggest context-aware completions in the writer's style. Support the remaining modules with operator review: generate draft content, answer questions, summarize, rewrite and track revisions. 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 publishable drafts linked to their sources. Retain the explicit scope boundary: One fixed style guide and licensed source set; final fact-checking and editorial judgment remain human.

What the build depends on. Source upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity editorial work requires specialist review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed style guide and licensed source set; final fact-checking and editorial judgment 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 editorial package. Offer a monthly production allowance after repeat demand. Quote complex multi-source or specialist editorial work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded editor-approved publishable draft linked to its sources. 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 tool switching and revision cycles while keeping the writer's voice and source traceability. Demonstrate a concrete editor-approved publishable draft linked to its sources using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Writers, editors and content teams 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 publishable draft linked to its sources from a small authorized input set, with a transparent calculation of accepted drafts per editorial hour and corrections after editorial approval and no promised savings.

The first 30 days

1. Week 1: interview five writers, editors and content teams producing source-based articles, briefs and scripts and inspect a recent example of drafts, prompts, revisions and approvals scattered across separate tools.
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 drafts per editorial hour and corrections after editorial 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 drafts per editorial hour and corrections after editorial 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 drafts per editorial hour and corrections after editorial 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 publishable drafts linked to their sources. 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, source 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 content teams producing source-based articles, briefs and scripts. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

HyperWrite, Prose Fusion and Lex are the tools buyers use today, alongside generic writing assistants and manual editing. Compare this product with the buyer's present method on accepted drafts per editorial hour and corrections after editorial 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, storage, reviewer hours, client revision rounds and licensed source material. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of editor-approved publishable drafts linked to their sources. 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. One fixed style guide and licensed source set; final fact-checking and editorial judgment remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.