Multi-platform ad campaign production workbench

For

Marketing teams and agencies running paid campaigns across several advertising platforms

Solves

Ad copy, creative concepts, briefs, targeting and budget decisions sit in separate subscriptions, so campaigns launch slowly and brand and performance data stay scattered.

Delivers

Team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs

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 campaign production cycles while keeping brand and performance decisions under team control.

1. Generate ad copy for each platform.
2. Produce original campaign concepts and storyboards.
3. Launch and manage campaigns across platforms from one place.
4. Create multiple ad copy variations for testing.
5. Enforce brand tone, style and visual identity rules.
6. Adjust campaigns from performance data.
7. Draft strategic campaign briefs.
8. Recommend audiences and targeting per channel.
9. Save ads from the web for reference.
10. Analyze creative elements against performance.
11. Produce many ad variants at once.
12. Write ad copy in multiple languages.
13. Customize tone and style per brand voice.
14. Shift budget to top-performing channels and ads.
15. Route content through team review and approvals.
16. Enrich leads and track campaign outcomes.
17. Edit images and video for ad creatives.
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 team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs with source references and unresolved questions.

Everything these tools do, in one app

• Ad copy generation Automatically creates advertising text for campaigns.Found in promoted.com, AI Ad Text Generator, Lexi AI and 2 more
• Creative concept generation Produces original ideas and concepts for ad campaigns.Found in Daydrm.ai, Protaigé, Ava Studio
• Multi-platform campaign launch Launches and manages ad campaigns across multiple advertising platforms from one place.Found in Pixel, Postly, Lexi AI
• Ad copy variations Generates multiple versions of ad copy for testing and optimization.Found in promoted.com, AI Ad Text Generator, Ava Studio and 1 more
• Brand consistency controls Keeps ad outputs aligned with brand guidelines, tone, and visual identity.Found in Protaigé, Ava Studio, AI Ad Text Generator
• Campaign performance optimization Continuously adjusts campaigns to improve results based on performance data.Found in Lexi AI, Pixel, MagicBrief
• Strategic brief generation Creates detailed strategic briefs to guide campaign development.Found in Daydrm.ai, Ava Studio, Protaigé
• Audience targeting recommendations Suggests target audiences and improves ad targeting across channels.Found in Lexi AI, Pixel
• Ad inspiration saving Captures and stores ads from the web for reference and inspiration.Found in MagicBrief
• Storyboard creation Visually plans and structures ad narratives.Found in MagicBrief, Ava Studio
• AI-driven creative analysis Analyzes ad creative elements to identify what drives performance.Found in MagicBrief
• Bulk ad creation Produces many ad variants at once for large-scale testing.Found in Ava Studio, Postly
• Multi-language ad support Creates ad copy in multiple languages.Found in AI Ad Text Generator, FusionOS.ai
• Tone and style customization Adjusts the tone and style of ad copy to match brand voice.Found in AI Ad Text Generator
• Real-time budget reallocation Shifts ad spend to top-performing channels and ads in real time.Found in Pixel
• Team collaboration and approvals Enables team workflows and approval processes for ad content.Found in Postly, MagicBrief
• Lead enrichment Enriches leads and tracks campaign outcomes for sales and marketing.Found in Pixel
• Integrated media editors Provides built-in image and video editing tools for ad creatives.Found in Postly

What goes in, what comes out

The workflow

1. In
   Start with

   Brand guidelines, product facts, audience data and past campaign results

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect brand guidelines

4. 3

   Product facts

5. 4

   Audience data and past campaign results

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs

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 kit and approved platform set; final brand, legal and spend decisions remain with the marketing team. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Campaign brief and brand kit, Editable creative production preview, Client proof and delivery. Use a thumbnail gallery for campaigns, a large central editing canvas, and a right-hand panel for brand rules, audience data and comments. Let users compare ad variants side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant asset. Make the task-specific outcome team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs 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

Brand-owned guidelines, product data and permitted campaign results. Cloud asset storage, design-file import/export and advertising platform 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 ad copy for each platform; produce original campaign concepts and storyboards. 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 agencies running paid campaigns across several advertising platforms use it to solve "ad copy, creative concepts, briefs, targeting and budget decisions sit in separate subscriptions, so campaigns launch slowly and brand and performance data stay scattered"?
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 ad variants per production hour and performance after launch.
4. Measure, then decide. Track approved ad variants per production hour and performance after launch; 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 kit and approved platform set; final brand, legal and spend decisions remain with the marketing team. Implement one approved input format, a bounded representative case set and the first two task modules: generate ad copy for each platform; produce original campaign concepts and storyboards. Support the third module with operator review: launch and manage campaigns across platforms from one place. 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 team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs. Retain the explicit scope boundary: One fixed brand kit and approved platform set; final brand, legal and spend decisions remain with the marketing team.

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 creative QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed brand kit and approved platform set; final brand, legal and spend decisions remain with the marketing team.

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 video, 3D or specialist design separately. These are test prices, not market benchmarks. Package the initial sale as one bounded team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs. 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 campaign production cycles while keeping brand and performance decisions under team control. Demonstrate a concrete team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

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

Lead magnet

A reviewed sample team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs from a small authorized input set, with a transparent calculation of approved ad variants per production hour and performance after launch and no promised savings.

The first 30 days

1. Week 1: interview five marketing teams and agencies running paid campaigns across several advertising platforms and inspect a recent example of ad copy, creative concepts, briefs, targeting and budget decisions sitting in separate subscriptions.
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 approved ad variants per production hour and performance after launch, 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 ad variants per production hour and performance after launch. 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 ad variants per production hour and performance after launch; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs. 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 rules, platform specs 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 paid campaigns across several advertising platforms. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

FusionOS.ai, promoted.com, Daydrm.ai, Protaigé, MagicBrief, AI Ad Text Generator, Ava Studio, Postly, Lexi AI and Pixel, plus freelancers and in-house production. Compare this product with the buyer's present method on approved ad variants per production hour and performance after launch. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, video or 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 team-approved ad copy, concepts, briefs and launch-ready variants linked to platform specs. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve brand voice, source attribution, claim accuracy and usage permissions. Marketing teams approve substantive changes and publication scope. One fixed brand kit and approved platform set; final brand, legal and spend decisions remain with the marketing team. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.