Brand relevance is now defined by what we see and what we hear. From the high-energy “vibes” of a short-form social clip to the strategic precision of a live sports broadcast, the most impactful data your business generates is no longer just text. It’s a mix of visuals, voices and, simply put, the vibe.
Until now, “video analytics” usually meant just scratching the surface by analyzing user comments or basic transcripts while leaving the most valuable signals on the table. The real story — the brand logos on screen, the energy in a creator’s voice or the specific music shift that signals a new trend — often remained just out of reach for traditional data stacks.
Snowflake Cortex AI multimodal capabilities are changing that. As a unified AI data platform designed to support multimodal workloads — text, documents, images, audio and video — Snowflake allows you to transform raw media into structured, queryable intelligence to help organizations unlock new revenue streams, while reducing the need to manage complex systems, performance headaches or unnecessary data movement.
Modern organizations no longer have the luxury of manual oversight in an era of infinite content. For luxury icons, where brand perception is the primary moat, protecting that intangible value is a mission-critical operation. To stay competitive, these leaders are shifting from simple detection to deep, programmatic intelligence. By leveraging Cortex AI Functions, organizations move beyond basic mentions to capture the true cultural context of a video, analyzing vocal sentiment, background music and visual “vibes” to ensure every appearance aligns with their high-end heritage.
As content scales, so does the demand for automated brand safety. Modern teams resolve the paradox of speed versus control by using programmatic moderation to flag risks in real time, ensuring creator partnerships remain brand-safe. This now extends to the front lines of security as deepfakes and synthetic media grow more sophisticated and organizations use AI to analyze pixels and audio waveforms for potential anomalies. By joining these signals with transaction data natively in Snowflake, organizations can more quickly detect potential fraud patterns before they impact customer trust.
This transformation even redefines sports intelligence, replacing manual entry with automated metadata pipelines that turn gameplay into structured, queryable assets. Ultimately, Cortex AI allows the modern organization to stop merely observing content and start mastering it, protecting the prestige of their brand while unlocking new monetization across a complex digital landscape.
With Snowflake, you can extract structured intelligence from media files as easily as querying a standard table. Below are three powerful ways organizations are using Cortex AI Functions to power programmatic video metadata extraction, effectively decoding the “vibes” of their content and customer interactions to drive high-stakes decision-making.
Marketing teams aren’t just looking for “mentions”; they are mining for the next big campaign idea. For example, identifying how products are used in unsponsored “lifestyle” videos, brands can pivot their creative strategy to match how customers actually use their products. These insights can help redirect ad spend toward high-performing “vibes” or to launch new product lines based on user trends.
The winners in today’s market reduce the “time to insight.” By leveraging Snowflake’s Cortex AI Functions, you shift from building complex systems to building customer relationships.
Your data now has a voice, a vision and a vibe.
In a call center, a transcript might look fine, but the vibe reveals a customer at their breaking point. Imagine being able to detect “anger signals” in vocal delivery — companies can trigger immediate retention workflows. Teams can use the insights from audio-based sentiment analytics to coach agents by spotting where professionalism drops or empathy matters most, and can also combine customer “anger level” with CRM data to automatically alert a senior account manager and prevent churn.
Sports leagues can create new proprietary metrics that drive betting markets, fan engagement and coaching insights by extracting time-stamped metadata, Instead of relying on human analysts to log every play, AI can automatically identify players, classify actions like passes, shots and fouls, and attach precise timestamps to each event.
When you look at traditional cloud service providers (CSPs), multimodal analytics usually looks like a sprawling diagram of interconnected services. At Snowflake, we believe that if you have to move data and manage infrastructure, it isn’t actually simple.
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