Source-based SEO content production workspace

For

Marketing teams and content agencies producing SEO articles at regular volume

Solves

Content is generated in one tool, optimized in another, scheduled in a third, and the source references and brand voice are lost between them.

Delivers

Editor-approved SEO articles linked to their sources

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

Reduce tool switching and rework while keeping every published article traceable to its sources and approved brand voice.

1. Generate article drafts from briefs and source material.
2. Score drafts against SEO rules and suggest fixes.
3. Place target keywords and related terms naturally.
4. Analyze top search results to shape structure.
5. Apply templates for ads, emails and social posts.
6. Produce content in multiple languages.
7. Support multi-user collaboration on one project.
8. Schedule and publish to chosen channels.
9. Store analyses, projects and reports.
10. Offer AI writing and editing suggestions.
11. Scrape permitted web sources for research.
12. Generate supporting images.
13. Summarize and visualize performance data.
14. Allow custom prompts and workflow steps.
15. Manage references from text, CSV, PDF and media.
16. Apply saved brand voice styles.
17. Show real-time on-page guidance for titles and meta descriptions.
18. Benchmark drafts against top-ranking pages.
19. Compare the reviewed result with the recorded baseline and value assumptions.
20. Capture corrections and named-owner approval before publishing.
21. Export a versioned editor-approved SEO article with source references and unresolved questions.

Everything these tools do, in one app

• AI content generation Automatically creates written content such as blog posts and articles from user inputs.Found in Scalenut, Blog Post Generator, NeuronWriter and 7 more
• SEO optimization Improves content to rank better in search engines using suggestions and scoring.Found in Scalenut, Blog Post Generator, NeuronWriter and 5 more
• Keyword integration Incorporates relevant keywords into content to enhance search visibility.Found in Scalenut, Blog Post Generator, NeuronWriter and 3 more
• SERP analysis Analyzes top Google search results to guide content structure and keywords.Found in NeuronWriter, SEO AI Writer, SEO.ai
• Content templates Provides pre-designed formats for different content types like ads, emails, and social posts.Found in Seio, Mark Copy AI, Contents.com and 1 more
• Multilingual support Allows content creation in multiple languages for global audiences.Found in Blog Post Generator, Contents.com, SEO.ai
• Team collaboration Enables multiple users to work together on content projects.Found in NeuronWriter, Seio, Mark Copy AI and 1 more
• Content scheduling and publishing Plans and automates posting content to various channels.Found in Mark Copy AI, SEO Content Machine
• Content management Organizes and stores content analyses, projects, and reports.Found in NeuronWriter, Somme.ai
• AI writing assistance Helps generate and edit content with AI-powered suggestions.Found in NeuronWriter, SEO.ai
• Content scraping Gathers information from web sources for research and inspiration.Found in SEO Content Machine
• Image generation Creates relevant images to complement written content.Found in SEO AI Writer
• Data analysis Summarizes and visualizes information to provide insights.Found in Seio
• Customizable workflows Allows users to modify AI prompts and processes for specific needs.Found in SEO AI Writer
• Context management Integrates and manages references like text, CSV, PDFs, and media to enrich content.Found in Somme.ai
• Custom writing styles Creates and applies personalized tones to maintain consistent brand voice.Found in Somme.ai
• Real-time SEO guidance Provides instant tips for on-page optimization like title tags and meta descriptions.Found in SEO.ai
• Competitor benchmarks Compares content performance against top-ranking pages.Found in SEO.ai

What goes in, what comes out

The workflow

1. In
   Start with

   Licensed source material, keyword sets, brand style rules and editorial constraints

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect licensed source material

4. 3

   Keyword sets

5. 4

   Brand style rules and editorial constraints

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Editor-approved SEO articles 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 brand style set and licensed source pool; final fact checks and publication decisions remain editorial. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Source and brief intake, Editable article workspace, Client proof and delivery. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for sources, keywords, 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 paragraph. Make the task-specific outcome editor-approved SEO articles linked to their sources 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

Client-owned source documents, authorized research sources and permitted web pages. Cloud asset storage, CMS 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

   6 days

   One buyer segment, one recurring use case; first modules: generate article drafts from briefs and source material; score drafts against SEO rules and suggest fixes; place target keywords and related terms naturally. 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

   3 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 marketing teams and content agencies producing SEO articles at regular volume use it to solve "content is generated in one tool, optimized in another, scheduled in a third, and the source references and brand voice are lost between them"?
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 articles per editorial hour and corrections after publication.
4. Measure, then decide. Track accepted articles per editorial hour and corrections after publication; 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 brand style set and licensed source pool; final fact checks and publication decisions remain editorial. Implement one approved input format, a bounded representative case set and the first three task modules: generate article drafts from briefs and source material; score drafts against SEO rules and suggest fixes; place target keywords and related terms naturally. 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 SEO articles linked to their sources. Retain the explicit scope boundary: One fixed brand style set and licensed source pool; final fact checks and publication decisions remain editorial.

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: One fixed brand style set and licensed source pool; final fact checks and publication decisions remain editorial.

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 article package. Offer a monthly production allowance after repeat demand. Quote complex multilingual or specialist campaigns separately. These are test prices, not market benchmarks. Package the initial sale as one bounded editor-approved SEO articles linked to their 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 rework while keeping every published article traceable to its sources and approved brand voice. Demonstrate a concrete editor-approved SEO articles linked to their sources using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Marketing teams and content agencies producing SEO articles at regular volume 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 SEO articles linked to their sources from a small authorized input set, with a transparent calculation of accepted articles per editorial hour and corrections after publication and no promised savings.

The first 30 days

1. Week 1: interview five marketing teams and content agencies producing SEO articles at regular volume and inspect a recent example of content generated in one tool, optimized in another, scheduled in a third, and the source references and brand voice lost between them.
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 accepted articles per editorial hour and corrections after publication, 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 articles per editorial hour and corrections after publication. 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 articles per editorial hour and corrections after publication; 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 SEO articles 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 rules and review examples, together with reliable delivery for a narrow content niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for marketing teams and content agencies producing SEO articles at regular volume. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Scalenut, Blog Post Generator, NeuronWriter, Seio, Mark Copy AI, SEO AI Writer, Contents.com, SEO Content Machine, SEO.ai and Somme.ai, used today as separate rented subscriptions. Compare this product with the buyer's present stack on accepted articles per editorial hour and corrections after publication. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, image 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 SEO articles linked to their sources. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve brand voice, source attribution, quotation accuracy and usage permissions. Editors approve substantive changes and publication scope. One fixed brand style set and licensed source pool; final fact checks and publication decisions remain editorial. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.