Input: three to five photos, names, date, and venue
Output: a 15-20 second invitation clip
Aspect: 9:16
Build log
1. Set the rule
I opened the photos, names, event date, and mood references, locked names, date, and the selected photos, and wrote down what could not change.
2. Run one minimum version
I made one small a 15-20 second invitation clip first. The names blurred during animation, so I held the text still and moved only the background.
3. Build the focused variant
I reused the same reference and changed only one clean date block and three photos.
4. Review and export
I checked text, photo order, timing, and readability at full size, then exported the final 9:16.
Complete execution record
Task boundary and source gate
Treat AI wedding invitation video as a deliverable, not a definition. The job receives three to five photos, names, date, and venue and owes a 15-20 second invitation clip in 9:16. Write the rejection reason first, then turn it into the first hard constraint.
Require identity permission, photo quality, date format, venue cue, dress code, tone, and the RSVP or reply path. Do not change body identity, add guests, or place a private event at a recognizable private location without consent.
The imgmov route
Write names, date, venue, consent, tone, and the call to action before visuals. Use photos as references so people stay recognizable, then add readable details in the external editor.
Keep platform requirements outside the model prompt. The prompt can describe a scene; a named checklist records the crop, claim, consent, and console check that make it deliverable.
Lock the variables that cannot drift
Lock identity, clothing, venue features, invitation wording, date format, and emotional tone. Style may change; the people and event facts may not.
Put the locked fields at the top of the prompt, not at the end: The practical move is to lock names, date, and the selected photos and change only one clean date block and three photos. Save that prompt with the reference, ratio, and model so the next run starts from a decision instead of a guess.
Step-by-step build path
1) Set the rule: I opened the photos, names, event date, and mood references, locked names, date, and the selected photos, and wrote down what could not change. Leave one checkable artifact from this step; do not start the next until it exists. 2) Run one minimum version: I made one small a 15-20 second invitation clip first. The names blurred during animation, so I held the text still and moved only the background. Leave one checkable artifact from this step; do not start the next until it exists. 3) Build the focused variant: I reused the same reference and changed only one clean date block and three photos. Leave one checkable artifact from this step; do not start the next until it exists. 4) Review and export: I checked text, photo order, timing, and readability at full size, then exported the final 9:16. Leave one checkable artifact from this step; do not start the next until it exists.
Change one named variable per rerun: prompt, reference, camera, duration, model, ratio, or export crop. If two variables change together, a better output cannot be reused because nobody knows which fix worked.
Review gates and evidence
Faces stay recognizable, the date is readable, venue cues match reality, and the reply path survives the safe area.
Keep source, approved wording, rejected version, correction, credit cost, and final crop next to the asset. The record exists so the next reviewer can reproduce the decision without a chat thread.
Failure diagnosis and retry ladder
If identity drifts, use less motion and more real frames. If text competes with the scene, simplify the background instead of shrinking type.
Do not upgrade on hope. A 5-second Agnes Video probe is 10 credits. If the concept passes, Seedance 2.5 costs 90 credits at 480p or 195 at 720p for 5 seconds; Kling is 195 without audio or 245 with audio. Veo enters only when a 4/6/8-second cinematic bucket is genuinely worth 80/125/165 credits. Prove hook, subject, and rhythm first, then pay to clean up motion that already worked.
Versioning and handoff
Deliver a social teaser, save-the-date cut, and print or message version. Each version keeps its own readable event block.
The folder is boring on purpose: source, approved reference, generation settings, caption file, platform cuts, QA screenshots, and one correction line. A reusable asset is boring in the right way.
Why this is not a generic answer
The imgmov advantage is the chain: Asset Library preserves the subject reference, Canvas fixes shot order and first/last frames, the workspace routes Agnes to Seedance, Kling, or Veo only after proof, and your external editor adds captions and CTA without regenerating the media.
Do not change body identity, add guests, or place a private event at a recognizable private location without consent. If the request only asks what ai wedding invitation video means, a search page is faster. This page is useful when someone must deliver a 15-20 second invitation clip under real constraints.
Frequently asked questions
What is the one rule I keep repeating?
The practical move is to lock names, date, and the selected photos and change only one clean date block and three photos.
The workflow is specific about its stopping point: it starts with three to five photos, names, date, and venue and stops at a 15-20 second invitation clip. In imgmov, upload the source, lock it as a reference, set 9:16, run one proof, and save the passing settings. If a reviewer cannot tell which version is approved, the workflow has failed even when the media looks good.
What do I check before export?
Names, dates, photo order, text stability, and final crop.
Do not upgrade on hope. A 5-second Agnes Video probe is 10 credits. If the concept passes, Seedance 2.5 costs 90 credits at 480p or 195 at 720p for 5 seconds; Kling is 195 without audio or 245 with audio. Veo enters only when a 4/6/8-second cinematic bucket is genuinely worth 80/125/165 credits. Prove hook, subject, and rhythm first, then pay to clean up motion that already worked.
What makes this different from a generic generator?
I start from three to five photos, names, date, and venue and keep a 15-20 second invitation clip consistent, instead of inventing a new scene each run.
The check is not “does it look AI-nice?” It is: Faces stay recognizable, the date is readable, venue cues match reality, and the reply path survives the safe area. Then the source, approved copy, rejected version, correction, and final crop stay in the same handoff folder.
What should I do if the first render drifts?
Cut the motion, lock the reference, and rerun one small version before batching.
If identity drifts, use less motion and more real frames. If text competes with the scene, simplify the background instead of shrinking type. Change one named variable, keep the old version, and record the credit cost. If the same failure repeats, fix the reference or scope rather than asking the prompt for forgiveness.