Multimodal models need video. We froze time to give it to them
PostHog introduced a new capability to convert session recordings into structured, multimodal-ready data formats. This allows LLMs to ingest and analyze user session video data directly for automated insights.
Verified State Diff
Impact & Verification Analysis
Product managers, data analysts, and developers using PostHog for user behavior analytics.
It significantly reduces the time-to-insight for user experience research by automating the analysis of session recordings, transforming a high-volume storage cost into a high-value data asset.
Full Fact Overview
PostHog is addressing the 'dark data' problem of session recordings by enabling the transformation of raw video playback data into a format compatible with multimodal large language models. By 'freezing time' and structuring these recordings, the platform allows developers to programmatically query user behavior patterns that were previously only accessible through manual observation. This integration bridges the gap between unstructured visual session data and AI-driven analytics, effectively turning dormant storage into actionable intelligence.