Tag: AWS Well-Architected Partners

MLOps applies DevOps principles to machine learning, enabling organizations to efficiently develop, deploy, and manage models at scale. Eviden’s 10-step MLOps assessment examines existing models, establishes governance, creates self-service access, scales data analysis, registers models, enables feature re-use, provides data access, tests models at scale, deploys models, and enables API access. This end-to-end approach streamlines model creation and deployment while ensuring governance and consistency.

Many organizations struggle with data silos and manual processes. Apps Associates helps companies build modern data platforms using Amazon Redshift, which consolidates data sources, reduces manual effort, and unlocks valuable insights. The Apps Associates accelerators quickly integrate data from ERP/CRM systems into Redshift to enable advanced analytics while driving cost reductions and revenue growth.

CyberCX built an AWS serverless data lake and data masking solution to enable using production data securely in non-production environments. The modular, AWS-native solution combines AWS services to mask sensitive data in near real-time while retaining data utility. This allows thorough testing and confidence before deployment to production, improving data security and accelerating time to market.

Many startups want to use machine learning but struggle with developing scalable MLOps pipelines. Automat-IT’s MLOps Accelerator helps startups fast-track their machine learning journey and provides an end-to-end automated solution for the ML lifecycle, from data preparation to deployment, leveraging AWS services. With customizable pipelines and dedicated ML experts, Automat-IT empowers various roles to develop, operationalize, and monitor models efficiently.

To grow with AWS, partners can pursue Competency designations which validate an organization’s expertise through rigorous assessment by AWS experts. By meeting requirements around projects, certifications, and capabilities, partners can demonstrate their proficiency and earn an AWS specialization badge in specific industries, use cases, or workloads. Attaining an AWS Competency distinguishes partners, but the preparation process also transforms practices.

Rapyder’s Call Agent Analyzer uses generative AI on AWS to revolutionize call center operations. It efficiently processes multilingual audio, summarizes calls, analyzes script adherence, and structures insights into actionable data. This solution helps businesses enhance customer satisfaction through data-driven call agent performance evaluation and training. As an AWS Partner, Rapyder provides cutting-edge cloud solutions that are reshaping industries like customer service.

Infosys is leveraging AWS generative AI capabilities like Amazon Bedrock and AWS Trainium to enhance its enterprise solutions. For example, Infosys Personalized Smart Video uses Amazon Bedrock to create rich, dynamic video content, while Infosys Cortex applies generative AI to analyze call transcripts and improve customer engagement. Overall, Infosys is rapidly adopting AWS’ flexible and scalable generative AI services to boost automation, productivity and user experience across its portfolio.

Crayon’s customizable landing zone accelerator automates setup of a secure, scalable AWS environment aligned to best practices. It establishes foundational accounts, applies baseline security controls, and integrates AWS services across the organization to drive cloud adoption for companies migrating to AWS while also improving governance for existing customers. Crayon guides customers through the landing zone build and subsequent workload migration, providing automation kits to speed deployments.

Darwinbox wanted to reduce the time to infer resumes against job descriptions using PyTorch models. AWS Premier Partner Minfy helped them leverage Amazon SageMaker and AWS Inferentia to compile models with Neuron SDK and deploy them, achieving 87% faster inference without retraining. Key steps were compiling models with the Neuron SDK, extending SageMaker containers, using Inference Recommender to optimize configurations, and sending requests in mini-batches.

Wipro’s next-generation dealer and distributor management system (DMS) provides an omnichannel, microservices-based solution enabling complete visibility and integrated management of all dealer operations. By leveraging AWS’s scalable, reliable, and secure cloud infrastructure, the solution offers benefits like improved analytics, reduced costs, high availability, and faster time-to-market. Wipro provides dealers a modern DMS that addresses advanced requirements around mobile access, IoT, and AI.