How We Created a Lakme-Inspired AI UGC Video: A Complete AI Video Generation Case Study
Introduction
AI video generation is no longer just about making experimental visuals. It is quickly becoming a serious production tool for brands, agencies, creators, and marketing teams that want faster content creation without compromising on storytelling.
Recently, our team experimented with creating a Lakme-inspired beauty UGC video entirely with AI tools. The idea was to build a reel that looked premium, relatable, natural, and scroll-stopping, without conducting a traditional shoot. The final output was designed to feel like creator-led content rather than a polished television commercial.
The project focused on a beauty product narrative around “One-&-Done Skin Tint,” using AI for scripting, visual generation, character consistency, voiceover, music selection, and final editing. The entire workflow was completed in approximately 48 hours, proving how human creativity and AI speed can work together when the process is planned properly.
Project Objective / Goal
The main goal was simple but challenging: create a premium-looking beauty reel that feels natural, relatable, and UGC-style, without a traditional shoot.
The video had to connect with women who want quick, everyday beauty solutions. The target audience included working professionals, entrepreneurs, side-hustlers, women with busy routines, and beauty users looking for convenience and speed.
Instead of showing the product in a highly polished ad film format, we wanted the video to feel like something a real creator would post on Instagram Reels. That meant the tone had to be conversational, the visuals had to feel handheld and natural, and the pacing had to match social media consumption habits.
The creative direction was built around real-life hustle moments, fast transitions, natural makeup looks, and relatable creator-style storytelling.
Planning & Concept Development
Before jumping into AI generation, the team began with a detailed debriefing process. This stage was important because AI tools can generate visuals quickly, but they need strong creative direction to produce meaningful results.
We first studied the Lakme-style campaign brief to understand the brand tone, product positioning, target audience, expected visual mood, social media format, and creator-style communication approach.
The central theme was “One-&-Done Skin Tint.” From there, the concept was shaped around the idea of a busy woman getting ready quickly while still looking polished and confident.
The creative approach was intentionally not made too glossy. A beauty TVC usually has perfect lighting, controlled studio movement, and highly polished product shots. For this experiment, the team wanted the video to feel more like a creator filming herself during a real day.
That decision influenced everything that followed – the script, camera style, lighting, character look, shot framing, transitions, music, and editing pace.
AI Tools & Platforms Used
The workflow used multiple AI platforms, each for a specific role.
ChatGPT was used during the early ideation and planning stage. It helped with structuring the concept, building the narrative, and thinking through how the video could move from one moment to another.
Claude was used for deeper prompt engineering and refinement. The team used Claude’s Opus and Sonnet models to create detailed scene-wise prompts. This helped improve clarity, consistency, and control over the final generated scenes.
Higgsfield was used for the final AI video generation. The team fed the script, prompts, character reference, and product assets into Higgsfield, using the Seedance 2.0 model for video creation.
Envato’s royalty-free library was used for background music. This helped avoid licensing issues while still giving the video a polished, campaign-ready sound. The voiceover was generated directly within Higgsfield, which made the workflow smoother and reduced dependency on external voice tools.
Script & Storyboarding Process
The script was not written as a generic product ad. It was developed like a short creator-led beauty reel.
The team focused on building a tight narrative that could work within a short video format. Since the product story was about quick and convenient beauty, the script had to reflect speed, ease, and confidence.
Once the script was ready, it was broken down into scenes. Each scene was planned according to the timeline of the video. This helped the team decide what should happen in every few seconds – whether the character should look into the camera, apply the product, smile subtly, move through a routine, or show the product naturally.
This scene-by-scene planning made the AI video generation process more controlled.
Content Generation Workflow
The content generation workflow followed a clear production pipeline:
| Workflow Step | What Happened |
| Brief Deconstruction | The team first broke down the campaign requirement into smaller parts. This included the product theme, audience, desired tone, and expected visual style. |
| Moodboarding & Research | The next step was defining the UGC look. The team studied the kind of content that feels native to Instagram Reels – handheld shots, natural expressions, realistic skin texture, everyday settings, and fast-paced edits. |
| Scriptwriting | A short and sharp script was created based on the brief. The goal was to make the product feel useful in a real routine, not forced into a traditional ad structure. |
| Asset Preparation | The product image was prepared as one of the key inputs. Since the product had to appear clearly and consistently, the reference image helped guide the AI output. |
| Character Reference Creation | A character reference sheet was created to maintain visual consistency. This was essential because one of the biggest challenges in AI-generated videos is keeping the same face, hairstyle, expression style, and overall appearance across multiple shots. |
| Prompt Engineering | Each scene was converted into a detailed prompt. Instead of using one broad prompt for the whole video, the team created individual prompts for each shot. |
| Video Generation | The prompts, character reference, and product assets were used inside Higgsfield to generate the clips. This structured process helped avoid random outputs and gave the final video a stronger narrative flow. |
AI Video Generation Workflow
The AI video generation stage was the most experimental part of the project.
Each shot was generated individually. The prompts were written according to the exact requirement of that moment in the timeline. This included details like camera angle, facial expression, hand movement, lighting, background setting, skin texture, eye movement, product interaction, creator-style movement, handheld camera feel, and natural human behavior.
For example, instead of writing a basic prompt like “woman applying makeup,” the team used more specific direction. The prompt would include how the model should hold the product, what kind of expression she should have, how the lighting should fall on the face, and what kind of camera movement should be present.
This level of detail helped make the AI output feel more realistic.
The team also used shorter clips wherever necessary. This was a practical decision because AI video tools can struggle with complex movements over longer durations. Shorter clips made it easier to control expressions, hand gestures, and beauty-related actions.
Voiceover & Audio Creation
The voiceover was created directly within Higgsfield. This helped reduce production time because the team did not need to record a human voiceover or use a separate audio generation tool.
The voiceover had to match the UGC style of the video. It could not sound too formal or too polished. The tone needed to feel like a creator explaining a quick beauty routine to her audience.
The goal was to keep the voice natural, clear, conversational, social-media friendly, and aligned with the beauty category. This helped the video feel more authentic and less like a hard-sell advertisement.
Music & Sound Design
Music was sourced from Envato’s royalty-free library. The selection had to support the beauty and lifestyle tone of the reel without overpowering the product message.
For a UGC-style beauty video, music plays a subtle but important role. It helps set the pace, makes transitions smoother, and gives the video a polished finish.
The music direction was kept light, modern, stylish, reel-friendly, and premium without becoming too dramatic. Since the video was built for social media, the sound had to support quick viewing and easy engagement.
Editing & Post-Production
Although most of the video was generated through AI, post-production played a major role in making the final output feel complete.
The editing process included selecting the cleanest generated clips, stitching individual clips into one seamless sequence, adding background music, adding supers and on-screen text, adjusting pacing, ensuring the product message was clear, removing outputs that felt too artificial, and creating a smoother flow between scenes.
The supers were especially important because they helped highlight the key product messages. In short-form content, viewers may not always listen to the audio immediately, so on-screen text gives the message a stronger chance of landing.
Even though the post-production work was light, it made a big difference. It turned separate AI-generated clips into a polished, campaign-ready reel.
Challenges Faced
AI made the production faster, but it did not make the process completely effortless. The team faced several challenges during creation.
Maintaining face consistency was one of the biggest challenges. AI often generated slightly different facial features from scene to scene. To solve this, the team used reference images and generated multiple variations. The best outputs were then selected to maintain continuity.
Unrealistic hand movements were another issue. Beauty videos often involve hand movements, product holding, and makeup application. These are still difficult areas for AI video tools. Sometimes the hand movement looked unnatural or the product interaction did not feel realistic.
Makeup application realism also required attention. Applying product on the face, showing skin texture, and making the movement feel real required several prompt refinements.
Some visuals initially looked overly polished or artificial. This was not suitable for a UGC-style beauty video. To solve this, the prompts were refined with more human and creator-style details such as handheld camera movement, natural eye movement, realistic skin texture, soft expressions, real-life lighting, and casual creator-style framing.
Optimizations & Improvements
The team improved the workflow through repeated testing and regeneration.
One of the most useful optimizations was moving from broad prompts to highly detailed scene-specific prompts. This allowed better control over each shot.
Another improvement was using shorter clips. Instead of forcing AI to generate long, complex actions, the team broke the video into smaller moments. This made it easier to manage expressions, gestures, and transitions.
The team also learned that references matter. The product image and character reference sheet gave the AI a stronger foundation. Without these references, the output would have been less consistent.
The final quality improved because of three things working together: strong creative direction, clear prompting, and careful editing decisions. This is an important learning for any AI content creation workflow. AI can generate fast, but creative judgment decides what is actually usable.
Time & Workflow Efficiency
The complete production took approximately 48 hours.
The first phase focused on preparation: research, moodboarding, scriptwriting, product reference preparation, and character reference creation.
The second phase focused on execution: prompt engineering, video generation in Higgsfield, clip selection, voiceover, music, editing, and assembly.
In a traditional shoot, the same kind of output may require a larger team, model coordination, product setup, location, lighting, camera crew, makeup, shoot time, and post-production. AI reduced many of those dependencies.
However, the process still needed human thinking at every stage. The speed came from AI, but the structure came from the team.
Final Results & Output
The final output was a polished UGC-style beauty video inspired by Lakme’s product world. It was created entirely through an AI-assisted workflow, using product images, a character reference sheet, scene-wise prompts, AI video generation, voiceover, music, and editing.
The reel achieved the intended creative direction: premium beauty look, natural creator-style feel, relatable everyday routine, clear product messaging, smooth short-form pacing, realistic character presentation, and social media-ready output.
Most importantly, the video did not feel like a random AI experiment. It followed a proper production pipeline from idea to final output.
Key Learnings & Best Practices
Start with the brief, not the tool. The tool should not decide the idea. The brief, audience, and message should guide the workflow.
References improve consistency. Product images and character references are essential when creating brand-led AI videos.
Scene-by-scene prompting works better. Breaking the video into smaller scenes gives better control over the output.
Shorter clips are easier to manage. Short clips reduce the chances of distorted hands, unnatural expressions, or unrealistic movement.
Editing still matters. AI generation is not the final step. Selection, sequencing, music, supers, and pacing turn the raw clips into a finished video.
Human creativity is still the differentiator. AI speeds up execution, but the strongest results come from human storytelling, visual judgment, and creative direction.
Future of AI Video Creation
AI video generation is becoming a powerful part of the modern content production pipeline. For brands, it opens up new possibilities: faster campaign testing, lower dependency on physical shoots, rapid UGC-style content creation, more visual experimentation, faster concept-to-output timelines, and scalable content for social media.
But the future is not just about replacing shoots. It is about expanding what creative teams can do.
AI can help teams test ideas faster, create multiple versions, explore different looks, and build content even when budgets or timelines are tight. At the same time, human direction will continue to remain important because brands still need taste, strategy, and storytelling.
The best AI videos will not come from prompts alone. They will come from teams that understand both creativity and production.
Conclusion
This Lakme-inspired AI UGC video experiment showed how a complete AI production pipeline can work in a real-world content scenario. From brief deconstruction and moodboarding to scripting, character reference creation, prompt engineering, Higgsfield video generation, voiceover, music, and editing, every stage required planning and creative decision-making. The biggest takeaway is clear: AI can make production faster, but human creativity makes the output meaningful.
When creative teams combine strong storytelling with the speed of AI tools, they can produce high-quality, social-first videos in a fraction of the usual time. For beauty, fashion, lifestyle, and product-led brands, this opens up a new way to create content that is fast, flexible, and visually engaging.
Want to create AI-generated videos for your brand? Our team can help with scripting, AI video creation, voiceovers, editing, and social-first content production for platforms like Instagram Reels and YouTube Shorts. Explore our AI video production services here: AI Video Production Services
FAQs
What is AI video generation?
AI video generation is the process of using artificial intelligence tools to create video content from prompts, scripts, images, references, or other inputs. It allows creators and brands to produce visual content faster than traditional production methods.
Can AI create UGC-style videos?
Yes, AI can create UGC-style videos when the workflow is planned properly. The key is to use natural prompts, realistic character references, handheld camera direction, conversational scripts, and social-media-friendly editing.
Which tools were used in this AI video workflow?
The workflow used ChatGPT and Claude for ideation, scripting, and prompt engineering. Higgsfield was used for video generation and voiceover, while Envato was used for royalty-free background music.
How long did the AI video production take?
The full production process took approximately 48 hours, including research, scripting, moodboarding, character reference creation, prompt engineering, video generation, and final editing.
What was the biggest challenge in creating the AI video?
The biggest challenge was maintaining face consistency across shots. AI often changes facial features slightly between generations, so reference images and multiple output variations were used to improve continuity.
Is AI video generation faster than traditional shooting?
Yes, AI can be much faster for certain types of content, especially short-form social videos. However, strong creative direction, prompt refinement, and editing are still required to achieve professional results.
Can AI replace traditional video shoots?
AI may not fully replace traditional shoots, especially for complex productions. But it can become a powerful alternative for concept videos, UGC-style ads, product experiments, social content, and fast campaign testing.
