Observed Signal · Jun 4, 2026 · Recognition · Source: https://martechseries.com/feed/ · Impact: 4/5 · Sentiment: Positive
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.
AWS competency recognition and Bedrock availability signal validated video-AI capabilities on a major cloud platform, enabling enterprise adoption, archive migration programs, and tighter cloud-product integration relevant to AdTech/MarTech vendors and media companies.
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Key Takeaways & Evidence Grounding
- TwelveLabs earned the Amazon Web Services (AWS) AI Competency.
- TwelveLabs’ Marengo 3.0 and Pegasus 1.2 models are available on Amazon Bedrock; Pegasus 1.5 is planned.
- TwelveLabs and AWS launched a program to migrate petabyte-scale video archives; migration partners include Cloudfirst.io and Iron Mountain.
- TwelveLabs collaborates with Amazon S3 and S3 Vectors service teams to operationalize video intelligence on AWS.
- TwelveLabs CEO Jae Lee is a member of the AWS Customer Advisory Board; a broadcast news customer reported a 10x increase in metadata coverage using TwelveLabs.
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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 Marengo Now in Amazon Bedrock Knowledge Base
TwelveLabs announced that its Marengo video model is now available as an embedding model inside Amazon Bedrock Managed Knowledge Base. This integration enables managed semantic video search on AWS, allowing customers to search video by meaning using natural language without building custom infrastructure. The service handles ingestion, indexing, and search automatically, with no vector database to provision. Customers can connect their video sources like Amazon S3 and search across visual scenes, speech, and audio. The solution supports metadata filters and keeps data within the customer's AWS account for regulated industries. Joint customer Iconik, a media asset management platform from Backlight, is among the first to use the integration, making semantic search a native capability. Iconik also became TwelveLabs' first Premier Tier ecosystem partner.
Intellias Achieves AWS AI Services Competency
Intellias, an AI-enabled product engineering and digital solutions partner, has earned the AWS AI Services Competency, placing it among AWS partners validated for implementing generative AI solutions at scale on AWS infrastructure. AWS validated Intellias through a technical assessment and multiple production customer implementations, including: migrating an aerial-imagery ML pipeline to an AWS serverless architecture with a tenfold reduction in total cost of ownership; building a generative AI analytics assistant that reduced time-to-insight to eight seconds; unifying marketing data across six sources into a multi-agent AI platform that cut campaign brief creation from days to under an hour; and delivering a GraphRAG solution that cut map-data validation time by up to 60%. Intellias says the designation supports collaboration with AWS to accelerate responsible, production-ready AI adoption.
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