{"id":1892,"date":"2026-01-14T16:51:38","date_gmt":"2026-01-14T16:51:38","guid":{"rendered":"https:\/\/b2bblogs.redbangle.com\/?p=1892"},"modified":"2026-02-23T04:22:41","modified_gmt":"2026-02-23T04:22:41","slug":"gen-ai-microdrama","status":"publish","type":"post","link":"https:\/\/staging.blogs.makerrs.com\/index.php\/2026\/01\/14\/gen-ai-microdrama\/","title":{"rendered":"Shaanu Ka Viva \u2013 A GenAI Microdrama for Bharat"},"content":{"rendered":"\n

Microdramas for the Scroll Generation<\/h2>\n\n\n\n

India has always loved drama. From saas-bahu serials to masala movies to gully cricket commentary. And today\u2019s young India – Bharat – wants it faster, funnier and scrollable.<\/p>\n\n\n\n

In this new internet-first world, a fresh format has quietly taken over the feed: the microdrama. Short, self-contained stories under a minute long, they borrow the structure of classic TV serials, shrink it, and remix it for the algorithm. And while microdramas can take many forms, the ones that stick for the Bharat audience often have a familiar flavour – a touch of entertainment, cultural nuance, and local relatability.<\/p>\n\n\n\n

The rise of this format is no surprise in a country where over a billion smartphones are in use, nearly 900 million people are online, and almost two-thirds of the population is under 35. Together, this scale of connectivity and a young, mobile-first audience has created the perfect conditions for bite-sized stories to flourish<\/a>.<\/p>\n\n\n\n

Making a Microdrama Series with Gen AI<\/h2>\n\n\n\n

We knew microdramas were working. So we asked ourselves – what if we made one? And what if we didn\u2019t use real life actors or cameras, but GenAI?<\/p>\n\n\n\n

As an agency constantly experimenting with emerging tools, we were already deep in the world of generative AI. But most AI content floating around felt like a demo reel. It was interesting, but not so entertaining. What if we used GenAI to tell a story people would actually want to watch? Something funny, scroll-first, and full of flavour of everyday desi drama.<\/p>\n\n\n\n

That\u2019s how Shaanu Ka Viva<\/em> came to life. A school-based microdrama series built using GenAI – but rooted in the kind of local humour and familiarity that makes Bharat laugh.<\/p>\n\n\n\n

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Building the World of Shaanu ka Viva<\/h2>\n\n\n\n

We wanted something small, repeatable, and funny. So we built a world that was easy to return to, and even easier to relate to. A small town school. A likeable teacher. And an over smart student.<\/p>\n\n\n\n

Shaanu is every overconfident student you\u2019ve met. He talks big, studies little, and thinks reels are a valid source of science. Sitting across from him is his exhausted teacher, still holding onto the hope that one day, Shaanu might get something right. In each episode, Shaanu is put through a viva, and somehow, always manages to give the wrong answer, delivered with full confidence and zero doubt.<\/p>\n\n\n\n

We chose this duo and a viva situation because their chemistry taps into a deeply desi memory: the classroom and the exams. Every Indian has lived some version of it. Plus, from an AI production lens, it gave us the right kind of constraints: a recurring classroom, two characters and a simple format. That made it easier to maintain visual consistency and focus more on the jokes. Each episode was under 1 minute, designed to land like a punchline. We kept the language Hindi for mass appeal, and to stay true to the world we were building.<\/p>\n\n\n\n

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Designing an AI Production Process<\/h2>\n\n\n\n

We treated AI like any other craft, with intention and precision. Cracking the look of Shaanu and Sir took the most time. For a series like this, the humour rests considerably on expressions, body language, and relatability. But the biggest issue with GenAI was consistency. You\u2019d get one good frame, and then the next one would have a completely different facial features, or a new hairstyle.<\/p>\n\n\n\n

We spent days experimenting with prompt structures, reference inputs, and image variations to get Shaanu\u2019s \u201cconfident but clueless\u201d face and Sir\u2019s \u201cperpetually disappointed\u201d look just right. However, generating these looks was one thing. Keeping them consistent was another. This meant layering tools, manually retouching key frames, and building a master visual template to ensure continuity. Here\u2019s the what the process evolved to:<\/p>\n\n\n\n

1. Character Definition<\/strong>
Mapping out each character\u2019s look, expressions, and quirks to carry the humour without it feeling generic<\/p>\n\n\n\n

2. Prompt Experimentation
<\/strong>Testing different prompts and references to achieve consistent faces and body language frame after frame<\/p>\n\n\n\n

3.<\/strong> Visual Reference System<\/strong>
Creating a master reference library to lock the characters\u2019 appearance across all episodes<\/p>\n\n\n\n

4.<\/strong> Base Image Generation<\/strong>
Producing core images for every scene, angle, and expression<\/p>\n\n\n\n

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5. Lip-sync and Animation<\/strong>
Applying basic animation to bring dialogues to life and keep the storytelling dynamic<\/p>\n\n\n\n

6.<\/strong> Manual Clean-up<\/strong>
Retouching frames to fix inconsistencies and sharpen details<\/p>\n\n\n\n

7. Voice Recording<\/strong>
Used real voice actors to deliver timing and energy that AI audio couldn\u2019t replicate<\/p>\n\n\n\n

8. Sound and Music Design<\/strong>
Layering sound effects and background scores to enrich the humour and pace<\/p>\n\n\n\n

9. Editing for Scroll<\/strong>
Cutting episodes into tight, punchy videos optimised for short-form, mobile-first viewing<\/p>\n\n\n\n

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The Tools We Used<\/h2>\n\n\n\n