Source-linked content and campaign operations console

For

Marketing teams and agencies running content and paid campaigns across several platforms

Solves

Content drafting, campaign experiments and cross-platform reporting sit in separate rented tools, so approvals, evidence and account changes are hard to trace.

Delivers

Approved content drafts, experiment verdicts and shipped ad changes

Built in

about 5 weeks of creation time, MVP in 5 days

Investment

$14,000 for the MVP, $47,500 for the full product

Run it

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

Reduce tool sprawl and keep every content draft, experiment and ad change source-linked and approved.

1. Generate articles, blogs and social posts from approved briefs.
2. Suggest context-aware edits for clarity and tone.
3. Brainstorm ideas from brand and audience context.
4. Apply customizable output styles per channel.
5. Publish approved content to connected CMS.
6. Generate ROAS and CPA hypotheses from account data.
7. Ship approved changes to Google Ads in one click.
8. Track each experiment on a kanban board to verdict.
9. Run statistical tests on experiment outcomes.
10. Apply optimization approaches beyond platform defaults.
11. Connect Google Analytics, Search Console, Google Ads, Meta Ads and LinkedIn Ads.
12. Create and manage PPC campaigns across platforms.
13. Support keyword research and Google Sheets content updates.
14. Monitor analytics and ad performance in real time.
15. Deliver consolidated reports to Slack or email.
16. Query cross-platform data through a connected AI client.
17. Make supported ad changes inside Google Ads and LinkedIn Ads in conversation.
18. Manage authentication and API connections through hosted servers.
19. Pull extra context from Tag Manager and Search Console.
20. Compare the reviewed result with the recorded baseline and value assumptions.
21. Capture corrections and named-owner approval before consequential use.
22. Export a versioned approved content drafts, experiment verdicts and shipped ad changes with source references and unresolved questions.

Everything these tools do, in one app

• AI text generation Generates written content such as articles, blogs, and social media posts.Found in NYX
• Context-aware editing Provides editing suggestions to improve clarity and tone.Found in NYX
• Idea brainstorming Helps users overcome writer's block by generating ideas.Found in NYX
• Customizable output styles Allows users to adjust output to match different writing styles.Found in NYX
• CMS integration Connects with popular content management systems.Found in NYX
• Hypothesis generation Generates hypotheses to improve ROAS or CPA based on account data and expert experience.Found in GoodLads
• One-click change approval Ships approved changes to Google Ads in one click, with no changes going live without user approval.Found in GoodLads
• Kanban experiment tracking Tracks each experiment on a kanban board from proposal to verdict.Found in GoodLads
• Statistical testing Uses statistical testing to determine experiment outcomes, with verdict timing dependent on click volume and impact size.Found in GoodLads
• Alternative optimization approaches Applies optimization approaches that differ from Google's built-in recommendations, such as reducing target CPA instead of increasing budget.Found in GoodLads
• Marketing tool integration Integrates with major marketing tools such as Google Analytics, Search Console, Google Ads, Meta Ads, and LinkedIn Ads.Found in Toffu AI
• Automated PPC campaign management Automates creation and management of PPC campaigns across multiple platforms including Google, Meta, and LinkedIn.Found in Toffu AI
• SEO support Provides keyword research, content generation for blogs and social posts, and updates via Google Sheets.Found in Toffu AI
• Real-time performance monitoring Monitors analytics and ad performance in real time with instant adjustments based on data.Found in Toffu AI
• Consolidated reporting Pulls data from various sources and delivers insights directly to Slack or email.Found in Toffu AI
• Cross-platform data querying Queries and analyzes data from Google Ads, LinkedIn Ads, Google Analytics 4, Google Tag Manager, and Search Console through a connected AI client.Found in HireOtto
• In-conversation ad changes Makes supported changes inside Google Ads and LinkedIn Ads without leaving the conversation.Found in HireOtto
• Hosted authentication and API Hosted MCP servers manage authentication and API connections, requiring no local setup.Found in HireOtto
• Additional context from Tag Manager and Search Console Provides additional context during account investigation via Tag Manager and Search Console.Found in HireOtto

What goes in, what comes out

The workflow

1. In
   Start with

   Brand guidelines, account data, campaign history and platform exports

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect brand guidelines

4. 3

   Account data

5. 4

   Campaign history and platform exports

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Approved content drafts, experiment verdicts and shipped ad changes

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, statistical tests and reproducible checks. Review source-linked explanations and uncertainty before accepting results. One connected ad account set and approved brand style guide; final publishing, budget changes and campaign verdicts remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Brand and channel setup, Content and experiment workbench, Approval and delivery. Use a thumbnail gallery for campaigns and drafts, a large central editing canvas, and a right-hand panel for sources, constraints and comments. Let users compare content versions and experiment variants side by side. Display draft, changes requested, approved and shipped states. Provide a client preview link with comments anchored to the relevant asset. Make the task-specific outcome approved content drafts, experiment verdicts and shipped ad changes 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

Google Analytics, Search Console, Google Ads, Meta Ads, LinkedIn Ads, Google Tag Manager, connected CMS and Slack or email. 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: generate articles, blogs and social posts from approved briefs; suggest context-aware edits for clarity and tone. 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 marketing teams and agencies running content and paid campaigns across several platforms use it to solve "content drafting, campaign experiments and cross-platform reporting sit in separate rented tools, so approvals, evidence and account changes are 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: Approved assets per marketing hour and verified campaign changes per review cycle.
4. Measure, then decide. Track approved assets per marketing hour and verified campaign changes per review cycle; 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 connected ad account set and approved brand style guide; final publishing, budget changes and campaign verdicts remain human. Implement one approved input format, a bounded representative case set and the first two task modules: generate articles, blogs and social posts from approved briefs; suggest context-aware edits for clarity and tone. Support the remaining modules with operator review: brainstorm ideas, apply output styles, publish to CMS, generate hypotheses, ship approved changes, track experiments, run statistical tests, apply alternative optimization, connect platforms, manage PPC campaigns, support keyword research, monitor performance, deliver reports, query cross-platform data, make in-conversation changes, manage authentication and pull Tag Manager and Search Console context. 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 approved content drafts, experiment verdicts and shipped ad changes. Retain the explicit scope boundary: One connected ad account set and approved brand style guide; final publishing, budget changes and campaign verdicts 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 campaign work requires specialist marketing QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One connected ad account set and approved brand style guide; final publishing, budget changes and campaign verdicts 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 campaign package. Offer a monthly production allowance after repeat demand. Quote complex multi-platform or specialist campaign work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded approved content drafts, experiment verdicts and shipped ad changes. 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 sprawl and keep every content draft, experiment and ad change source-linked and approved. Demonstrate a concrete approved content drafts, experiment verdicts and shipped ad changes using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Marketing teams and agencies running content and paid campaigns across several platforms professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample approved content drafts, experiment verdicts and shipped ad changes from a small authorized input set, with a transparent calculation of approved assets per marketing hour and verified campaign changes per review cycle and no promised savings.

The first 30 days

1. Week 1: interview five marketing teams and agencies running content and paid campaigns across several platforms and inspect a recent example of content drafting, campaign experiments and cross-platform reporting sitting in separate rented tools.
2. Week 2: prepare a consented or synthetic demonstration of the stated task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure approved assets per marketing hour and verified campaign changes per review cycle, 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: Approved assets per marketing hour and verified campaign changes per review cycle. 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

Approved assets per marketing hour and verified campaign changes per review cycle; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs approved content drafts, experiment verdicts and shipped ad changes. 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 brand styles, campaign constraints and review examples, together with reliable delivery for a narrow marketing niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for marketing teams and agencies running content and paid campaigns across several platforms. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

NYX, GoodLads, Toffu AI, HireOtto, freelancers, agencies and platform-native tools. Compare this product with the buyer's present method on approved assets per marketing hour and verified campaign changes per review cycle. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, platform API calls, 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 approved content drafts, experiment verdicts and shipped ad changes. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve brand voice, source attribution, claim accuracy and usage permissions. Marketers approve substantive changes and publishing scope. One connected ad account set and approved brand style guide; final publishing, budget changes and campaign verdicts remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.