VERIDIVE - We're building Agentic Knowledge & Discovery Platform for spoken content.

# Our Mission

Every day, millions of hours of spoken content are created across podcasts, YouTube, lectures, interviews, streams and conferences. It contains invaluable knowledge -- insights from experts, research findings, product reviews and ideas that shape industries. Yet the vast majority of this knowledge remains locked inside audio and video, unsearchable and undiscoverable.

VERIDIVE exists to unlock this knowledge. We deploy autonomous AI agents that process spoken content at scale, extracting entities, verifying facts, mapping connections and transforming raw audio into structured, searchable intelligence that anyone can explore.

# Who We Serve

• Researchers & Academics: discover cited studies, expert opinions, and cross-referenced findings across thousands of hours of lectures and interviews

• Journalists & Media: track expert commentary, fact-check claims, and find primary sources across spoken media

• Founders & Product Teams: monitor competitor mentions, track industry trends, and gather market intelligence from podcast interviews

• Students & Learners: search lecture content, find explanations of complex topics, and build study knowledge bases

# What/How We Do

VERIDIVE transforms fragmented spoken content (video, audio, voice, transcript, conference, podcast) into a structured, interconnected and searchable Knowledge-Augmented Graph (KAG) platform. The core value is enabling users to move beyond simple search to perform deep semantic analysis, find hidden relationships and generate new content and insights.

VERIDIVE is a petabyte-scale intelligence engine, not just another chat interface.

VERIDIVE has hybrid MPP architecture, graph database and vector database. This setup optimizes deep relational queries for Knowledge-Augmented Generation (KAG) while ensuring high-performance semantic retrieval for Retrieval-Augmented Generation (RAG).

VERIDIVE

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