AdAtlas AI

AdAtlas AI — Turning Ad Creatives into Measurable Intelligence

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Inspiration

Ad performance is often measured by surface-level metrics — impressions, clicks, conversions — but those only reveal outcomes, not causes. We were driven by one question: what if ad platforms could understand why certain creatives succeed?

Most systems measure audience behavior, not creative quality. We wanted to quantify the emotional tone, color balance, and pacing of ads, and link these to measurable performance signals such as CTR (Click-Through Rate) and virality.

This inspired us to build AdAtlas AI, a platform that fuses vision, audio, and marketing intelligence into a unified creative understanding framework.

What it does

AdAtlas AI interprets ad creatives across multiple modalities visual, audio, and emotional and extracts performance-related insights. In under five minutes, it analyzes any video or image ad and provides a breakdown of its creative effectiveness.

It identifies:

  • Emotional tone and mood progression

  • Object and brand element detection

  • Speech pacing and sentiment alignment

  • Color and visual consistency

  • Predicted CTR and virality scores (via Reka QuickTag)

  • Cross-creative similarity trends (via ChromaDB)

These insights can directly inform recommendation models, ad ranking algorithms, and creative benchmarking dashboards.

How we built it

Backend — FastAPI + Asynchronous AI Pipeline

Our backend, built with FastAPI, uses an asynchronous event-driven pipeline for parallelized multimodal processing.

FFmpeg extracts frames and audio tracks from videos, ensuring consistent temporal sampling.

OpenCV computes color-tone averages, motion intensity, and scene transitions.

Gemini 2.5 Flash/Pro performs frame-level object detection, mood classification, and narrative summarization.

Groq Whisper transcribes and embeds speech, generating semantic and tonal representations.

Reka QuickTag predicts CTR, virality, and emotional tone distribution, linking creative elements to marketing performance.

ChromaDB Cloud stores and indexes embeddings for similarity search and trend comparison.

Each subsystem runs concurrently, with data merging at the orchestration layer. Average analysis time: 2.5 minutes per creative.

Frontend — React + Modern UI Frameworks

The frontend was built with React.js, HTML, Tailwind CSS, and Vanilla JavaScript for speed and responsiveness. We combined multiple UI frameworks ShadCNn UI, Acertinity UI, Cult UI, Magic UI, and Material UI to create a consistent design system.

Frontend highlights:

  • Upload ad creatives (video or image) for instant processing

  • Real-time progress visualization

  • Emotion, tone, and visual object summaries

  • CTR and virality graphs

  • Interactive similarity map powered by embedding distances

  • Color and narrative progression charts

    Challenges we ran into

  • Multimodal Synchronization: Aligning visual, auditory, and semantic data streams in real time.

  1. Latency Management: Balancing asynchronous API calls across Gemini, Groq, and Reka while preserving throughput.

  2. Visualization Overload: Presenting dense analytical data in an intuitive, non-technical interface.

  3. Embedding Storage: Optimizing ChromaDB queries for fast creative similarity results.

Accomplishments that we're proud of

  • Engineered a fully asynchronous multimodal analysis pipeline integrating five AI systems.

  • Reduced total processing time to under 5 minutes per ad.

  • Designed embedding-based creative similarity using ChromaDB Cloud.

  • Developed a responsive, elegant frontend dashboard using seven integrated UI frameworks.

  • Delivered a project that fits five major tracks AppLovin, Reka, Groq, Chroma, and Y Combinator with clear value for each.

What we learned

  • Orchestrating asynchronous multimodal AI systems at scale requires strict dependency management.

  • Reka QuickTag’s marketing insight layer can predict engagement potential from creative tone alone.

  • Groq Whisper’s low-latency transcription accelerates real-time analysis.

  • ChromaDB embeddings are powerful for clustering and creative discovery.

  • True ad intelligence lies not in metrics, but in interpretation, understanding emotional and narrative structure.

What's next for AdAtlas AI

We are expanding AdAtlas AI into a full-scale creative intelligence SaaS platform designed for marketing teams, ad networks, and recommendation engines.

Planned Developments

  • Public API for creative benchmarking and real-time ad insight generation

  • Integration with Bright Data for live web trend enrichment

  • Elastic-based creative search engine for large-scale ad clustering

  • Correlation studies between tone, narrative pacing, and engagement metrics

  • Y Combinator incubation track: evolving AdAtlas into a scalable startup offering insight-driven creative analytics

Our long-term goal is to make creativity measurable transforming subjective design into interpretable, actionable data.

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