Managed AI visual production and review platform

For

Creative teams and marketing groups producing campaign and product visuals

Solves

Visual work is spread across several rented generation, editing and animation tools, so assets, styles and approvals live in different places.

Delivers

Reviewed visual assets linked to a named approver

Built in

about 6 weeks of creation time, MVP in 7 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

Consolidate generation, editing, animation and review into one owned workspace.

1. Generate images from written prompts.
2. Edit and refine generated or existing images.
3. Apply approved styles and themes.
4. Export high-resolution files for professional use.
5. Process batches of prompts or images.
6. Expose an API for programmatic generation.
7. Run in a browser without third-party apps.
8. Provide an intuitive interface for all skill levels.
9. Return results quickly for rapid iteration.
10. Detect objects within images.
11. Tag visual elements with contextual labels.
12. Animate images into short videos.
13. Generate voiceovers from text.
14. Create headshots and presenter images from supplied photos.
15. Render text reliably inside generated images.
16. Organize work in a project library.
17. Support team collaboration and comments.
18. Capture corrections and named-owner approval before consequential use.
19. Export a versioned reviewed visual asset set with source references and unresolved questions.

Everything these tools do, in one app

• Text-to-Image Generation Creates images from written text prompts.Found in MidJourney for Web, Midjourney v7, Bing Create and 4 more
• Image Editing Tools Allows users to refine and adjust generated or existing images.Found in BrainFever, BasedLabs AI, Google Nano Banana Pro
• Style Customization Lets users choose or adjust artistic styles and themes for outputs.Found in MidJourney for Web, Midjourney v7, BrainFever and 3 more
• High-Resolution Output Produces images at high resolution suitable for professional use.Found in Midjourney v7, Imagen 2, ThinkDiffusion and 1 more
• Batch Processing Generates or processes multiple images at once to save time.Found in NymphLens, ThinkDiffusion
• API Access Enables programmatic image generation and integration into workflows.Found in NymphLens, Google Nano Banana Pro
• Web-Based Interface Provides direct access through a web browser without third-party apps.Found in MidJourney for Web
• User-Friendly Interface Offers an intuitive and easy-to-use design for all skill levels.Found in MidJourney for Web, Midjourney v7, Bing Create and 2 more
• Fast Processing Generates images quickly to allow rapid iteration.Found in Midjourney v7, Imagen 2, Google Nano Banana Pro
• Community-Driven Updates Features regular updates and improvements guided by user community.Found in MidJourney for Web, Midjourney v7
• Object Detection Automatically identifies objects within images.Found in NymphLens
• Image Tagging Categorizes visual elements with contextual tags.Found in NymphLens
• Video Animation Creates animated videos by adding motion to images.Found in BrainFever, BasedLabs AI
• Voiceover Generation Generates life-like voiceovers from text.Found in Autodraft
• AI Influencer Creation Generates personalized headshots and AI influencers from provided images.Found in BasedLabs AI
• Text Rendering in Images Reliably renders text within generated images for captions or interfaces.Found in Google Nano Banana Pro
• Project Organization Saves and manages creative works in a project library.Found in BrainFever
• Collaboration Tools Allows teams to work together on AI-driven creative content.Found in BasedLabs AI

What goes in, what comes out

The workflow

1. In
   Start with

   Approved prompts, brand references, source images and usage constraints

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect approved prompts

4. 3

   Brand references

5. 4

   Source images and usage constraints

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed visual assets linked to a named approver

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 approved brand style set and licensed source assets; final brand, legal and publication checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Brief and references, Editable production preview, Client proof and delivery. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for references, 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 asset. Make the task-specific outcome reviewed visual assets linked to a named approver 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 asset libraries, approved stock or licensed source images and publishing destinations. Cloud asset storage, design-file import/export and campaign delivery channels. 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

   7 days

   One buyer segment, one recurring use case; first modules: generate images from written prompts; edit and refine generated or existing images. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   8 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 creative teams and marketing groups producing campaign and product visuals use it to solve "visual work is spread across several rented generation, editing and animation tools, so assets, styles and approvals live in different places"?
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 production hour and corrections after brand review.
4. Measure, then decide. Track approved assets per production hour and corrections after brand review; 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 brand style set and licensed source assets; final brand, legal and publication checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: generate images from written prompts; edit and refine generated or existing images. Support the remaining modules with operator review: apply approved styles and themes; export high-resolution files; process batches; expose an API; detect objects; tag elements; animate images; generate voiceovers; create headshots; render text; organize projects; support collaboration. 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 reviewed visual assets linked to a named approver. Retain the explicit scope boundary: One approved brand style set and licensed source assets; final brand, legal and publication checks 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 creative QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One approved brand style set and licensed source assets; final brand, legal and publication checks 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 asset 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 reviewed visual asset set. 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

Consolidate generation, editing, animation and review into one owned workspace. Demonstrate a concrete reviewed visual asset set using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Creative teams and marketing groups producing campaign and product visuals professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed visual asset set from a small authorized input set, with a transparent calculation of approved assets per production hour and corrections after brand review and no promised savings.

The first 30 days

1. Week 1: interview five creative teams and marketing groups producing campaign and product visuals and inspect a recent example of visual work spread across several rented generation, editing and animation 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 approved assets per production hour and corrections after brand review, 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 production hour and corrections after brand review. 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 production hour and corrections after brand review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewed visual assets linked to a named approver. 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, brand constraints and review examples, together with reliable delivery for a narrow creative niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for creative teams and marketing groups producing campaign and product visuals. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

MidJourney for Web, Midjourney v7, Bing Create, BrainFever, NymphLens, Imagen 2, Autodraft, ThinkDiffusion, BasedLabs AI and Google Nano Banana Pro. Compare this product with the buyer's present method on approved assets per production hour and corrections after brand review. 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 reviewed visual assets linked to a named approver. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve brand voice, source attribution, likeness permissions and usage rights. Named approvers authorize substantive changes and publication scope. One approved brand style set and licensed source assets; final brand, legal and publication checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.