Video face and background replacement studio

For

Video editors and content teams producing branded footage with people and objects to remove or replace

Solves

Background removal, face replacement and object isolation live in separate tools, so editors export between subscriptions and lose control of source footage.

Delivers

Editor-approved replacement clips linked to source timecodes

Built in

about 5 weeks of creation time, MVP in 6 days

Investment

$14,500 for the MVP, $49,500 for the full product

Run it

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

Reduce tool switching and manual masking while keeping source footage and consent records under the client's control.

1. Remove backgrounds from videos and GIFs automatically.
2. Replace faces in photos and video with matched lighting and angle.
3. Isolate or remove specific people and objects from footage.
4. Refine edges for hair, glass and transparent materials.
5. Render high-resolution output without watermarks.
6. Preserve or replace audio in processed clips.
7. Process full-length clips in the cloud.
8. Generate closed captions from the final audio.
9. Generate subtitles in multiple languages.
10. Dub videos into over 20 languages.
11. Clone and generate voices with natural intonation.
12. Record screen with AI-assisted capture.
13. Apply quick automated edits.
14. Apply the brand kit to titles, colours and end cards.
15. Export to YouTube, Vimeo and Adobe Premiere Pro or After Effects.
16. Compare the reviewed result with the recorded baseline and value assumptions.
17. Capture corrections and named-owner approval before consequential use.
18. Export a versioned editor-approved replacement clip with source references and unresolved questions.

Everything these tools do, in one app

• Automated background removal Automatically removes backgrounds from videos and GIFs without manual selection.Found in Unscreen, Megaton Mask
• Face swapping Replaces faces in photos and videos with high precision and realism.Found in Swapface
• Object and people isolation Isolates or removes specific people and objects from video footage.Found in Megaton Mask
• High-resolution output Produces output in high resolution, maintaining clarity and detail.Found in Swapface, Unscreen
• No watermark Output videos have no watermark.Found in Unscreen
• Audio support Supports audio in processed videos.Found in Unscreen
• Full-length clip processing Handles full-length video clips.Found in Unscreen
• Plugin integration Integrates with Adobe Premiere Pro and After Effects via a plugin.Found in Unscreen
• API access Provides an API for developers to integrate functionality.Found in Unscreen
• Closed captioning Automatically generates closed captions for videos.
• Subtitling Generates subtitles in multiple languages.
• Dubbing Dubs videos into over 20 languages.
• Voice cloning Generates and clones voices with natural-sounding intonation.
• Screen recording Records screen with AI-powered tools.
• Instant video edits Performs quick automated video edits.
• Brand kit Maintains consistent visuals and style with an integrated brand kit.
• Platform integrations Integrates with platforms like YouTube and Vimeo.
• Edge refinement Refines edges for challenging elements like hair, glass, and transparent materials.Found in Megaton Mask
• Cloud processing Processes video in the cloud, reducing hardware requirements.Found in Megaton Mask
• User-friendly interface Provides an intuitive interface that simplifies the editing process.Found in Swapface, Megaton Mask
• File format support Supports various file formats for different projects.Found in Swapface
• Privacy and security Operates under strict privacy and security policies.Found in Swapface

What goes in, what comes out

The workflow

1. In
   Start with

   Licensed footage, consent records, brand assets and target faces

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect licensed footage

4. 3

   Consent records

5. 4

   Brand assets and target faces

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Editor-approved replacement clips linked to source timecodes

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 fixed output resolution and licensed face and voice set; final consent, likeness and publication checks remain editorial. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Footage and consent intake, Editable replacement preview, Client proof and delivery. Use a thumbnail gallery for projects, a large central preview canvas with a timeline, and a right-hand panel for masks, faces, captions and comments. Let users compare original and processed versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant timecode. Make the task-specific outcome editor-approved replacement clips linked to source timecodes 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

Client-owned footage, authorized interviews and permitted research 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.

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: remove backgrounds from videos and GIFs automatically; replace faces in photos and video with matched lighting and angle. 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 video editors and content teams producing branded footage with people and objects to remove or replace use it to solve "background removal, face replacement and object isolation live in separate tools, so editors export between subscriptions and lose control of source footage"?
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: Accepted clips per editing hour and corrections after client review.
4. Measure, then decide. Track accepted clips per editing 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 resolution and licensed face and voice set; final consent, likeness and publication checks remain editorial. Implement one approved input format, a bounded representative case set and the first two task modules: remove backgrounds from videos and GIFs automatically; replace faces in photos and video with matched lighting and angle. Support the third module with operator review: isolate or remove specific people and objects from footage. 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 editor-approved replacement clips linked to source timecodes. Retain the explicit scope boundary: One fixed output resolution and licensed face and voice set; final consent, likeness and publication checks remain editorial.

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 resolution and licensed face and voice set; final consent, likeness and publication checks remain editorial.

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 editor-approved replacement clip linked to source timecodes. 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 manual masking while keeping source footage and consent records under the client's control. Demonstrate a concrete editor-approved replacement clip linked to source timecodes using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Video editors and content teams producing branded footage with people and objects to remove or replace professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample editor-approved replacement clip linked to source timecodes from a small authorized input set, with a transparent calculation of accepted clips per editing hour and corrections after client review and no promised savings.

The first 30 days

1. Week 1: interview five video editors and content teams producing branded footage with people and objects to remove or replace and inspect a recent example of background removal, face replacement and object isolation living in separate tools, so editors export between subscriptions and lose control of source footage.
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 accepted clips per editing 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: Accepted clips per editing 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

Accepted clips per editing 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 editor-approved replacement clips linked to source timecodes. 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 masks, consent records 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 video editors and content teams producing branded footage with people and objects to remove or replace. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Swapface, Unscreen and Megaton Mask, plus freelancers, creative agencies and generic generation tools. Compare this product with the buyer's present method on accepted clips per editing hour and corrections after client 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 editor-approved replacement clips linked to source timecodes. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve likeness consent, source attribution, quotation accuracy and usage permissions. Named owners approve substantive changes and publication scope. One fixed output resolution and licensed face and voice set; final consent, likeness and publication checks remain editorial. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.