Klip AI

Paste a URL, get viral content.
Landing Page
Deep-Research and Planning
Session with AI Marketing Expert

Inspiration

Early-stage tech founders and builders know their product deeply, but most do not have the time, budget, or knowledge to advertise. As sudents and builders, we faced this issue ourselves; we coded many personal projects but didn't know where to find users. In this era, social media is one of the best methods for promotion. Klip AI started from one question: can a founder turn a website/application URL into social media reels in minutes?

What it does

Klip AI converts a startup’s public website URL into multiple short-form reels in under 10 minutes.

Flow:

Founder pastes a URL.
Our agent scrapes all pages in the website and extracts product messaging and key visuals.
Our agent does deep research to understand the context behind the product - market research, competitor analysis, and other information about the website on the internet. It also researches patterns in trending reels on social media so it can emulate those styles.
The agent generates one reel based on this research context.
The user has a session with an AI Marketing Director avatar which will ask questions about the user's style preferences for the reels.
The agent creates a plan for 3-5 more reels and generates them with this additional information.
Founder exports MP4 files and posts.

Speed-to-first-reel: No editing timeline, no design tools, no blank page.

How we built it

Scraping + capture: Browserbase StageHand for page discovery, screenshots, and text extraction.
Trend analysis: Engagement-weighted template scoring from current short-form format signals.
AI layer: Perplexity Sonar-based deep-researched content and LLM-generated hook/copy options mapped to product features and audience intent.
Video pipeline: HeyGen Video Generation API, Remotion + Google Veo for programmatic composition, transitions, and rendering.
Backend: FastAPI orchestration, Node
Frontend: React

Challenges we ran into

It was difficult for HeyGen's realtime Avatar API to converse when there was background noise, because of its auto VAD. So, we decided to optimize the auto VAD by implementing Kalman filters in the frontend to remove background noise before passing it into the avatar stream.
It was difficult to make the videos include accurate images of the website because LLMs/image models often hallucinate. So we used BrowserBase's Stagehand to dynamically take the best screenshots and images in the website when scraping it, then passed them into HeyGen.
Video generation is expensive. We parallelized jobs and generated reels before-and-after the session with the Marketing Director so users can see reels quickly.

Accomplishments we’re proud of

End-to-end pipeline from URL to downloadable reels.
Sub 6-minute generation for multiple reels.
We created reels for the founders and hackathon participants and posted them on Instagram: https://www.instagram.com/klip.techfounders?igsh=MzRlODBiNWFlZA==.
Being able to have a realtime/low-latency speech conversation with the AI avatar, which asks high-quality questions.
The content and visuals in the reels are accurate - no hallucinations.

What we learned

We learned that generating many reels is better than generating a single reel because users prefer multiple variations that they can post and A/B test quickly.
We gained technical skills in creating agents that do multi-turn conversations, web automation, video editing, research, and putting that all together in a pipeline that includes both sequential and parallel steps.