TwelveLabs raises $100M to bring superintelligence to AI video models

2026-07-01 · Source: AI – SiliconANGLE · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

TwelveLabs Inc., a developer of generative AI foundation models for video understanding, announced on July 01, 2026, it secured \$100 million in Series B funding, bringing its total raised to over \$207 million. Co-led by NEA and NAVER Ventures, with participation from Amazon and others, this capital aims to expand the company's technology beyond simple video comprehension to holistic intelligence. TwelveLabs has built frontier foundation models like the Marengo 3.0 and Pegasus 1.5 families, which natively understand video by maintaining persistent memory across queries, unlike traditional LLMs that segment video into screenshots. These models enable real-world AI embedding for various content types and convert video into structured data, facilitating advanced reasoning and operationalization across industries such as security, advertising, sports, and automotive. The company is also deepening its partnership with Amazon Web Services, committing to AWS Trainium chips and launching new models on AWS first.

Key takeaway

For Directors of AI/ML evaluating advanced multimodal capabilities, TwelveLabs' \$100 million funding signals a significant advancement in native video understanding. You should investigate models like Marengo and Pegasus for operationalizing video data, especially if your workflows in security, advertising, or automotive rely heavily on analyzing footage. This technology offers a path to more sophisticated reasoning by maintaining persistent memory, moving beyond screenshot-based analysis.

Key insights

Machine intelligence's core substrate is recorded reality in motion, not language, enabling native video understanding.

Principles

• Video is the primary data for understanding.
• Native video understanding surpasses LLM segmentation.
• Persistent memory enhances AI video reasoning.

Method

TwelveLabs constructs multimodal foundation models from the ground up to natively understand video, maintaining persistent memory between queries for compounding intelligence.

In practice

• Embed AI for video, audio, text, and composition.
• Convert video into structured data for LLM reasoning.
• Analyze and search footage in security or automotive.

Topics

• Video AI
• Foundation Models
• Multimodal AI
• TwelveLabs
• AWS Trainium
• Video Understanding
• AI Funding

Best for: Research Scientist, Investor, Director of AI/ML, AI Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI – SiliconANGLE.