
Prompt-to-video production workbench with managed review
Reduce tool switching and review cycles while keeping one consistent visual style.
- For
- Creative teams and studios producing short promotional and narrative video clips
- Solves
- Video concepts are generated across several rented tools, so characters, pacing and approvals drift between clips and nothing stays in one owned workflow.
- Delivers
- Reviewer-approved clip sets linked to a shot list
- Built in
- about 5 weeks of creation time, MVP in 6 days
- Investment
- $13,000 for the MVP, $44,000 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
Reduce tool switching and review cycles while keeping one consistent visual style.
- Generate video from text descriptions.
- Animate supplied still images into clips.
- Assemble multi-shot sequences with continuity.
- Keep characters consistent across scenes.
- Produce smooth motion in generated clips.
- Apply cinematic camera movements.
- Control narrative flow and pacing.
- Compose scenes from prompts for concept iteration.
- Iterate concepts quickly without full production.
- Produce short segments such as 5-second or 15-second clips.
- Run several generation jobs at once.
- Keep confidential projects private.
- Sign in with Google or Discord.
- Meter usage by credits with top-ups or subscriptions.
- Offer a free tier for basic trials.
- Capture corrections and named-owner approval before client delivery.
- Export a versioned reviewer-approved clip set linked to a shot list with source references and unresolved questions.
Everything these tools do, in one app
- Text-to-video generation Creates videos from simple text descriptions.Found in Luma Dream Machine 1.5, Seedance 2.0
- Image-to-video generation Animates static images into video clips.Found in Luma Dream Machine 1.5
- Multi-shot storytelling Produces sequences with multiple shots that maintain continuity.Found in Seedance 2.0
- Consistent character rendering Keeps characters looking the same across different scenes.Found in Seedance 2.0
- Smooth motion Generates fluid movement in videos.Found in Luma Dream Machine 1.5, Seedance 2.0
- Cinematic camera movements Adds professional-style camera moves to shots.Found in Luma Dream Machine 1.5, Seedance 2.0
- Narrative and pacing controls Lets users influence scene flow and timing.Found in Seedance 2.0
- Prompt-driven scene composition Builds scenes quickly from prompts for concept iteration.Found in Seedance 2.0
- Rapid iteration Enables quick testing of visual concepts without lengthy production.Found in Luma Dream Machine 1.5
- Short clip generation Produces brief video clips, such as 5-second or 15-second segments.Found in Luma Dream Machine 1.5, Deforum Studio
- Web and mobile access Available on web browsers and iOS devices.Found in Luma Dream Machine 1.5
- Social sign-in Allows login using Google or Discord accounts.Found in Deforum Studio
- Credit-based usage Uses credits for generation, with options for top-ups or subscriptions.Found in Deforum Studio
- Concurrent generations Runs multiple generation jobs at the same time.Found in Deforum Studio
- Private generation Keeps created content private for confidential projects.Found in Deforum Studio
- Free access Offers free options to try basic capabilities.Found in Seedance 2.0
What goes in, what comes out
- Text prompts
- Still images
- Character references
- Brand constraints
AI drafts, people review. Visual production platform with managed creative review.
- Reviewer-approved clip sets linked to a shot list
How it works
The workflow
- InStart with
Text prompts, still images, character references and brand constraints
- 1
Confirm the buyer's problem and scope
- 2
Collect text prompts
- 3
Still images
- 4
Character references and brand constraints
- 5
Then follow this sequence: 1
- OutFinish with
Reviewer-approved clip sets linked to a shot list
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 generation and continuity modules. Use deterministic code for credit accounting, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed output format and licensed asset set; final brand and legal checks remain human. A model suggestion is never a verified fact, professional decision or authorization to publish.
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 preview canvas, and a right-hand panel for prompts, character references, pacing controls and comments. Let users compare takes side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant shot. Make the task-specific outcome reviewer-approved clip sets linked to a shot list visible beside its evidence, review state and value baseline.
Accounts and administration
Project ownership, asset versions, client comments, approval states, credit allowances, generation 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 publishing.
Integrations and data access
Customer-owned prompt libraries, authorized image and character assets and permitted brand sources. Cloud asset storage, design-file 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.
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 video from text descriptions; animate supplied still images into clips; assemble multi-shot sequences with continuity. 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 creative teams and studios producing short promotional and narrative video clips use it to solve "video concepts are generated across several rented tools, so characters, pacing and approvals drift between clips and nothing stays in one owned workflow"?
- 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 clips per production hour and corrections after client review.
- Measure, then decide. Track approved clips per production hour and corrections after client 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 fixed output format and licensed asset set; final brand and legal checks remain human. Implement one approved input format, a bounded representative case set and the first three task modules: generate video from text descriptions; animate supplied still images into clips; assemble multi-shot sequences with continuity. 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 reviewer-approved clip sets linked to a shot list. Retain the explicit scope boundary: One fixed output format and licensed asset set; final brand and legal 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 fixed output format and licensed asset set; final brand and legal 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 video from text descriptions; animate supplied still images into clips; assemble multi-shot sequences with continuity. 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$44,000about 5 weeks of creation time · start with the MVP from $13,000
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
Creative teams and studios producing short promotional and narrative video clips run it inside the business: text prompts, still images, character references and brand constraints in, reviewer-approved clip sets linked to a shot list 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
#913327 - accent
#54b4c9 - surface
#f1e6e4 - ink
#22201e
- Headings
- Manrope
- Text
- Manrope
- 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 clip package. Offer a monthly production allowance after repeat demand. Quote complex long-form or specialist work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewer-approved clip set linked to a shot list. 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 review cycles while keeping one consistent visual style. Demonstrate a concrete reviewer-approved clip set linked to a shot list using the buyer's approved example and show the baseline, corrections and actual delivery effort.
Where to find buyers
Creative teams and studios producing short promotional and narrative video clips professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.
Lead magnet
A reviewed sample reviewer-approved clip set linked to a shot list from a small authorized input set, with a transparent calculation of approved clips per production hour and corrections after client review and no promised savings.
The first 30 days
- Week 1: interview five creative teams and studios producing short promotional and narrative video clips and inspect a recent example of video concepts generated across several rented tools, so characters, pacing and approvals drift between clips and nothing stays in one owned workflow.
- 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 clips per production hour and corrections after client 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 clips per production hour and corrections after client 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 clips per production hour and corrections after client review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.
Retention and expansion
Repeat the workflow when the buyer again needs reviewer-approved clip sets linked to a shot list. 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, character references 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 studios producing short promotional and narrative video clips. Repeatable delivery and useful integrations matter more than access to a base model.
Alternatives and positioning
Luma Dream Machine 1.5, Seedance 2.0 and Deforum Studio are what buyers use today, rented separately per seat or credit. Compare this product with the buyer's present method on approved clips per production hour and corrections after client review. Offer one owned workflow with combined features, customer data ownership and the buyer's own brand instead of several rented subscriptions. Market uniqueness and competitor coverage are not verified.
Main delivery costs
Generation attempts, video 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 reviewer-approved clip sets linked to a shot list. Track cost per accepted output, including correction work, unsuccessful cases and support.
Safeguards
Preserve brand voice, source attribution, likeness permissions and usage rights. Named owners approve substantive changes and publication scope. One fixed output format and licensed asset set; final brand and legal checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.