Brand and product shots
Generate product showcases, atmospheric footage, and concept visuals.
A standalone generative video workflow
AI Video focuses on footage, motion, atmosphere, and native audio. It is separate from Explainer Video and uses model-native generation rather than the knowledge storyboard and external-TTS pipeline.
Generate product showcases, atmospheric footage, and concept visuals.
Turn text or reference images into short-form motion clips.
Use Omni references and continue modifying the result in later turns.
Use the model-generated audio track and verify the final media contains audio.
Guide the opening state and ending target with images, adapted to each provider’s capabilities.
Omni can continue from the previous interaction to produce a revised version.
Review the model’s ratios, durations, resolutions, and edit capability.
Describe subjects, motion, camera, setting, and audio, then add images or attachments when needed.
Veo produces a single-turn result; Omni can continue through multi-turn editing.
A good result depends on the model, but also on a clear topic, audience, source material, and delivery format. These steps help you use KPainter for real teaching, training, and product education work.
Before using the AI Video Generator, define whether the content is for students, new hires, customers, sales teams, or internal experts. The audience determines depth, terminology, visual pacing, and the call to action at the end.
If the same topic needs to serve more than one audience, create a primary version first, then adapt it into a lesson opener, training recap, product explanation, or interactive practice activity. That keeps reuse high without turning the output into a generic content pile.
Break source documents, slides, topic notes, or knowledge points into context, key concepts, steps, examples, common mistakes, and conclusions. Clear structure gives the generation process a stronger path and makes the result easier to edit, review, and reuse.
For education teams, this maps to learning goals and classroom activities. For training teams, it maps to SOPs, job tasks, product features, and recurring questions. The structure decision before generation usually saves more time than heavy revision after output.
After generation, decide whether the output is for a classroom, training recap, product explanation, sales demo, or public sharing. The delivery context affects the title, cover, narration pace, and editing priorities.
If one topic needs to be reused over time, combine video, slides, visual summaries, and interactive lessons so the same knowledge asset can support different situations.
After delivery, keep improving the content based on class feedback, training questions, customer objections, or team review. Strong topics can grow into examples, practice tasks, FAQs, or course fragments.
Maintenance is more useful than one-off generation. Keep the version, use case, and next action clear so content can become part of a reusable team knowledge base.
AI Video directly generates short footage and native audio; Explainer Video plans knowledge structure, scenes, and narration before assembly.
Currently only Omni supports multi-turn conversation editing; Veo results do not expose the edit composer.
The page only shows public, reachable production results. Local or sandbox placeholders are not used.
Turn topics, lessons, SOPs, and product explanations into structured AI explainer videos for concept explanation, training, and product education.
Create precise vector animations for formulas, diagrams, algorithms, structures, and workflows across math, science, engineering, and product education.
Turn an idea or reference image into posters, covers, illustrations, product visuals, and social images with GPT Image and Nano Banana.
Choose inputs, ratio, duration, and resolution from the selected model’s real capabilities.