Observed Signal · Sep 10, 2026 · Product Launch · Source: https://martechseries.com/feed/ · Impact: 4/5 · Sentiment: Positive
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.
Major platform integration (AWS Bedrock) with a leading video AI vendor enabling new semantic search capabilities, relevant to MarTech and AI industries.
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Key Takeaways & Evidence Grounding
- TwelveLabs' Marengo model is now available as an embedding model in Amazon Bedrock Managed Knowledge Base for managed semantic video search.
- Pegasus 1.6, built on Pegasus 1.5, is released for physical AI, enabling egocentric video understanding for robots, drones, and autonomous vehicles.
- Pegasus 1.6 supports five core workflows: action segmentation, dense caption labeling, quality scoring, search/curation, and consent/compliance flagging.
- The Bedrock integration supports metadata filters and keeps all data within the customer's AWS account.
- Iconik is among the first customers using the Bedrock integration and became TwelveLabs' first Premier Tier ecosystem partner.
Connected Companies & Entities
“TwelveLabs, a leading video intelligence company, announced that its Marengo model is now available as an embedding model inside Amazon Bedr...”
“Amazon Bedrock Managed Knowledge Base, Amazon S3, and Amazon Agentic AI are mentioned.”
“Iconik, the cloud-native, API-first media asset management platform from Backlight, is among the first using Marengo through Amazon Bedrock ...”
Ontology Mapping & Concepts
Related Market Signals & Shifts
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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 Bedrock Introduces Managed Knowledge Bases
AWS released Managed Knowledge Bases for Amazon Bedrock on 17 June 2026. The feature lets Bedrock manage vector storage, indexing, embedding-model selection, and retrieval infrastructure for Retrieval-Augmented Generation (RAG) workloads, reducing operational overhead and accelerating time-to-value. The managed option can lower costs (S3-based storage, pay-per-ingest/retrieval), simplify embedding management, and suit proofs-of-concept, departmental uses, and variable workloads. Trade-offs include reduced visibility and control over the vector store, potential performance limits for very high QPS use cases, fewer advanced search/custom-ranking capabilities, and immature Infrastructure-as-Code support (CloudFormation/CDK). Teams requiring advanced search, fine-tuned indexing, or full IaC automation may prefer self-managed OpenSearch or other vector databases; a common IaC workaround today is a Lambda-backed Custom Resource that calls the Bedrock API during deployment.
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.
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