
Multi-format visual production and review workspace
Reduce tool switching and rework while keeping one approved visual version.
- For
- Small product, marketing and analytics teams producing websites, written content and dashboard mockups
- Solves
- Visual production is split across separate website builders, writing tools and dashboard mockup tools, so teams re-enter content, lose review history and cannot keep one approved version.
- Delivers
- Reviewed, exportable multi-format visual package
- Built in
- about 5 weeks of creation time, MVP in 6 days
- Investment
- $12,500 for the MVP, $42,500 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
Reduce tool switching and rework while keeping one approved visual version.
- Generate design templates from supplied briefs and brand inputs.
- Edit layouts and content by drag and drop.
- Assemble pages from pre-designed components and blocks.
- Check responsive behavior across device widths.
- Export clean production code for websites.
- Generate written content for articles, blogs and marketing copy.
- Apply tone and style settings for defined audiences.
- Offer real-time writing suggestions and grammar corrections.
- Connect to common writing and publishing platforms.
- Select from a template library for content formats.
- Start dashboards from a library of industry templates.
- Tailor designs with custom color palettes and element variations.
- Collect interactive comments and feedback for team collaboration.
- Export wireframes to BI tools such as Tableau and Power BI.
- Organize projects in managed workspaces.
- Compare the reviewed result with the recorded baseline and value assumptions.
- Capture corrections and named-owner approval before consequential use.
- Export a versioned reviewed, exportable multi-format visual package with source references and unresolved questions.
Everything these tools do, in one app
- AI-powered template generation Automatically generates design templates based on user inputs.Found in Loopple AI Website Builder
- Drag-and-drop editor Allows users to easily customize layout and content by dragging and dropping elements.Found in Loopple AI Website Builder, Mokkup.ai
- Pre-designed components Provides ready-made UI components and blocks for faster assembly.Found in Loopple AI Website Builder
- Responsive design Ensures designs look good on all devices.Found in Loopple AI Website Builder
- Code export Allows users to download clean, production-ready code.Found in Loopple AI Website Builder
- Content generation Generates written content for articles, blogs, and marketing copy.Found in Dezbor Beta
- Tone and style customization Lets users customize the tone and style to fit different audiences.Found in Dezbor Beta
- Real-time suggestions Provides real-time suggestions and grammar corrections while writing.Found in Dezbor Beta
- Integration capabilities Integrates with common writing and publishing platforms.Found in Dezbor Beta
- Template library Offers a library of templates for various content formats.Found in Dezbor Beta
- Dashboard templates Provides over 100 customizable dashboard templates for various industries.Found in Mokkup.ai
- Customizable elements Allows tailoring designs with custom color palettes and element variations.Found in Mokkup.ai
- Collaboration tools Enables interactive commenting and feedback for team collaboration.Found in Mokkup.ai
- Export to BI tools Exports wireframes directly to BI tools like Tableau and Power BI.Found in Mokkup.ai
- Workspace management Manages workspaces for organizing projects.Found in Mokkup.ai
What goes in, what comes out
- Brand assets
- Product facts
- Content briefs
- Data definitions
AI drafts, people review. Visual production platform with managed creative review.
- Reviewed
- Exportable multi-format visual package
How it works
The workflow
- InStart with
Brand assets, product facts, content briefs and data definitions
- 1
Confirm the buyer's problem and scope
- 2
Collect brand assets
- 3
Product facts
- 4
Content briefs and data definitions
- 5
Then follow this sequence: 1
- OutFinish with
Reviewed, exportable multi-format visual package
AI does the heavy lifting, people stay in charge
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three 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 brand system and one approved data schema per workspace; final brand, factual and data 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 brand inputs, Editable production canvas, Review and export. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for components, content, data fields and comments. Let users switch between website, written content and dashboard views of the same project. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant element. Make the task-specific outcome reviewed, exportable multi-format visual package 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 storage, content management and publishing destinations, BI tools such as Tableau and Power BI, and common writing platforms. 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.
How we build it
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
Scoping call
Day 1Thirty 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
MVP
6 daysOne buyer segment, one recurring use case; first modules: generate design templates from supplied briefs and brand inputs; edit layouts and content by drag and drop. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
7 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
3 weeksSelf-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe 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.
- Pick the riskiest assumption. Here: will small product, marketing and analytics teams producing websites, written content and dashboard mockups use it to solve "visual production is split across separate website builders, writing tools and dashboard mockup tools, so teams re-enter content, lose review history and cannot keep one approved version"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Approved assets per production hour and rework after approval.
- Measure, then decide. Track approved assets per production hour and rework after 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 brand system and one approved data schema per workspace; final brand, factual and data checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: generate design templates from supplied briefs and brand inputs; edit layouts and content by drag and drop. Support the third module with operator review: assemble pages from pre-designed components and blocks. 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, exportable multi-format visual package. Retain the explicit scope boundary: One brand system and one approved data schema per workspace; final brand, factual and data 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 and data QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One brand system and one approved data schema per workspace; final brand, factual and data checks remain human.
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- Phase 1
MVP
One buyer segment, one recurring use case; first modules: generate design templates from supplied briefs and brand inputs; edit layouts and content by drag and drop. Manual review in the loop.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$42,500about 5 weeks of creation time · start with the MVP from $12,500
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.
| Stage | Hosting and infrastructure | AI usage | Total per month |
|---|---|---|---|
| MVP and paid pilotabout 3 customers | $40–$80 | $150–$310 | $190–$390 |
| Full productabout 50 customers | $160–$320 | $2,100–$4,200 | $2,260–$4,520 |
Run it or resell it
For your own team
Small product, marketing and analytics teams producing websites, written content and dashboard mockups run it inside the business: brand assets, product facts, content briefs and data definitions in, reviewed, exportable multi-format visual package out, reviewed by your people.
As part of your offer
Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.
Your brand, or this one
Run it under your own brand, or start from this concept style.
- primary
#915627 - accent
#549ac9 - surface
#f1eae4 - ink
#22201e
- Headings
- Archivo
- Text
- Lora
- Voice
- Confident, visual, craft-proud
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 multi-brand or data-heavy dashboard work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed, exportable multi-format visual package. 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 one approved visual version. Demonstrate a concrete reviewed, exportable multi-format visual package using the buyer's approved example and show the baseline, corrections and actual delivery effort.
Where to find buyers
Small product, marketing and analytics teams professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.
Lead magnet
A reviewed sample reviewed, exportable multi-format visual package from a small authorized input set, with a transparent calculation of approved assets per production hour and rework after approval and no promised savings.
The first 30 days
- Week 1: interview five small product, marketing and analytics teams producing websites, written content and dashboard mockups and inspect a recent example of visual production split across separate website builders, writing tools and dashboard mockup tools, so teams re-enter content, lose review history and cannot keep one approved version.
- Week 2: prepare a consented or synthetic demonstration of the three task modules.
- Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
- Week 4: measure approved assets per production hour and rework after 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: Approved assets per production hour and rework after 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
Approved assets per production hour and rework after approval; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.
Retention and expansion
Repeat the workflow when the buyer again needs reviewed, exportable multi-format visual package. 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 systems, component sets, content styles and review examples, together with reliable delivery for a narrow production niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for small product, marketing and analytics teams producing websites, written content and dashboard mockups. Repeatable delivery and useful integrations matter more than access to a base model.
Alternatives and positioning
Loopple AI Website Builder, Dezbor Beta and Mokkup.ai used as separate rented subscriptions, plus manual design and writing work. Compare this product with the buyer's present method on approved assets per production hour and rework after 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, image and code 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, exportable multi-format visual package. Track cost per accepted output, including correction work, unsuccessful cases and support.
Safeguards
Preserve brand voice, source attribution, factual accuracy and usage permissions. Named owners approve substantive changes and publication scope. One brand system and one approved data schema per workspace; final brand, factual and data checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.