Observed Signal · Apr 20, 2026 · Technical Release · Source: https://martechseries.com/feed/ · Impact: 3/5 · Sentiment: Positive
TwelveLabs Launches Pegasus 1.5 Video Reasoning Model
TwelveLabs announced a set of product and ecosystem updates at NAB Show 2026, positioning itself as a full‑stack video intelligence platform. The company launched Pegasus 1.5, a video foundation model introducing Time‑Based Metadata Extraction (TBM) that discovers temporal boundaries and returns timestamped, schema‑compliant structured metadata in a single API call. TwelveLabs also introduced Rodeo, an application-layer creative co‑pilot that uses AI agents to help creators find, edit and assemble footage via natural language. The company announced a partnership with Autodesk to embed TwelveLabs‑powered Smart Search and Smart Actions into Autodesk Flow Capture (PIX), bringing search, automated tagging and workflow automation into existing production tools. Pegasus 1.5 is reported to be in production with a major broadcast network and claimed to outperform competing models in internal segmentation benchmarks.
Introduces production-grade video reasoning that can convert long-form video into queryable, timestamped metadata in a single API call, which is practically useful for publishers, broadcasters and brands but is a vendor-level technical release rather than a platform-level industry shift.
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Key Takeaways & Evidence Grounding
- TwelveLabs announced product and ecosystem advancements at NAB Show 2026.
- TwelveLabs launched Pegasus 1.5, which introduces Time‑Based Metadata Extraction to extract timestamped, schema‑compliant structured metadata from video in a single API call.
- TwelveLabs introduced Rodeo, an application‑layer AI creative co‑pilot that uses AI agents to find, edit, and assemble footage via natural language.
- TwelveLabs partnered with Autodesk to add Smart Search and Smart Actions to Autodesk Flow Capture (PIX) to enable natural‑language search, automated tagging, and media routing.
- In early testing, Pegasus 1.5 was reported to outperform a competing Gemini model (Gemini 2.5 Pro) by 30% on aggregate segmentation quality benchmarks and is already in production with a major broadcast network.
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TwelveLabs Raises $100M Series B for Video Superintelligence
TwelveLabs, a video intelligence company, announced a $100 million Series B round co-led by NEA and NAVER Ventures with participation from Amazon, Radical Ventures, Korea Investment Partners, Index Ventures, Quadrille Capital and Red Bull Ventures. The company is extending beyond video-understanding models into a full-stack, agentic video intelligence system that unites perception, knowledge and reasoning. TwelveLabs highlights its Marengo 3.0 video embedding model and Pegasus 1.5 model for turning video into structured data; both models are distributed via Amazon Bedrock and TwelveLabs’ API. AWS is described as TwelveLabs’ preferred cloud provider with a multiyear partnership that includes optimizing inference on AWS Trainium chips and launching new models first on AWS. The funding will be used to accelerate R&D, expand offices (San Francisco, Seoul, new New York and London offices) and move from foundation models to application-level products like Rodeo.
TwelveLabs Earns AWS AI Competency
TwelveLabs announced it has earned the Amazon Web Services (AWS) AI Competency, recognizing the company's technical proficiency and enterprise deployments of video-understanding AI on AWS. The designation builds on a strategic collaboration with AWS—including product integration with Amazon S3 and S3 Vectors, joint go‑to‑market programs, and a migration program for petabyte-scale video archives with partners Cloudfirst.io and Iron Mountain. TwelveLabs said its Marengo and Pegasus video‑understanding models are available on Amazon Bedrock (Marengo 3.0, Pegasus 1.2; Pegasus 1.5 coming soon). CEO Jae Lee serves on the AWS Customer Advisory Board. The company cited a customer case where a broadcast news organization increased metadata coverage by 10x using TwelveLabs technology.
TwelveLabs Marengo Now in Amazon Bedrock Knowledge Base
TwelveLabs, a video intelligence company, announced two major developments. First, its Marengo video model is now available as an embedding model in Amazon Bedrock Managed Knowledge Base, enabling managed semantic video search on AWS. This integration automates ingestion, indexing, and search, eliminating the need for custom infrastructure or vector databases, while supporting metadata filters and keeping data within the customer's AWS account. Second, TwelveLabs released Pegasus 1.6, a model for egocentric video understanding in physical AI applications, such as robots, drones, and autonomous vehicles. Pegasus 1.6 supports five workflows: action segmentation, dense caption labeling, quality scoring, search/curation, and consent/compliance flagging. It builds on Pegasus 1.5 with improved entity recognition and faster processing. The CEO, Jae Lee, emphasized the mission to help machines understand the world through video.
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