To keep up with fast-paced advancements in the technology industry, hardware and software company Cisco uses Amazon Web Services (AWS) to power its innovation.
Reported impact
Cisco unlocked a host of benefits by migrating to Amazon SageMaker, but it is not slowing down. As it continues its migration, Cisco’s Webex team is actively working on several features that harness AI, ML, and LLMs. Running these enormous models requires more sophisticated solutions.
To keep up with fast-paced advancements in the technology industry, hardware and software company Cisco uses Amazon Web Services (AWS) to power its innovation. After testing Amazon SageMaker in multiple environments, Cisco’s Webex team had immediate success. It quickly migrated its large models—spanning 3 environments and 10 different applications that require at least 1 model—to Amazon SageMaker while continuing to host the applications on Amazon EKS. Cisco deployed dozens of models on Amazon SageMaker endpoints. It also used NVIDIA’s Triton Inference Server, which supports model concurrency and scales globally across AWS data centers. Key services included Amazon Bedrock hosts the foundation models and generative ai application logic; Amazon SageMaker supports model training, tuning, deployment, or managed ml inference; Amazon Elastic Kubernetes Service runs containerized services and scales application workloads across clusters.
After testing Amazon SageMaker in multiple environments, Cisco’s Webex team had immediate success.
Founded in 1984, Cisco is a global hardware, software, and service company that seeks to help enterprises, commercial businesses, and consumers make powerful connections through advanced technology and support.
It quickly migrated its large models—spanning 3 environments and 10 different applications that require at least 1 model—to Amazon SageMaker while continuing to host the applications on Amazon EKS.
Over the years, Cisco has expanded significantly, employing over 71,000 people worldwide.
To keep up with fast-paced advancements in the technology industry, hardware and software company Cisco uses Amazon Web Services (AWS) to power its innovation.
When its growing artificial intelligence (AI) and machine learning (ML) models needed more resources, Cisco began hosting its models on a managed, purpose-built AWS solution to scale its models separately from its applic
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
Related
AWS Sample Sep 24, 2024 BT Group BT Group needed a secure, centrally governed way to scale generative AI beyond ad hoc experimentation, with cost control, privacy, prompt security, model monitoring, and flexibility to use multiple LLM providers without… Amazon Bedrock · Amazon SageMaker · GenAI Gateway AWS Sample Jul 7, 2024 Wildix Based in Estonia, Wildix has offered unified communications solutions since 2005 and provides services to 2 million users worldwide. The company focuses on enhancing its customers' sales processes through its… "Using AWS was crucial for our company to be able to move forward quickly and not miss this window of… AWS Lambda · Amazon Polly · Amazon Redshift AWS Sample Apr 17, 2024 Chunghwa Telecom Furthermore, Chunghwa Telecom needed a platform with robust security controls. To improve artificial intelligence (AI) data security and governance, the company migrated its generative AI projects to AWS. The first generative AI solution, the SDLC assistant, has saved developers an estimated 13 percent of their… Amazon Bedrock · Amazon Polly 