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"The session was also recommended to colleagues exploring cloud-native AI architectures."
The problem: 99acres' tech team was exploring AI adoption but needed practical context on enterprise implementation — including security, governance, scalability, and architectural decision-making — before moving beyond experimentation.
What edForce did: Delivered a live AWS edTalk on Agentic AI, covering Amazon Bedrock and how to think about security, governance, and scale before rolling AI out enterprise-wide.
The result: The session gave technology teams useful, real-world context for evaluating AI adoption — useful enough that it was recommended on to colleagues working on similar cloud-native AI architecture problems.
"Qubryx initiated internal discussions to evaluate AWS as a foundation for upcoming AI-driven initiatives and proof-of-concept programs."
The problem: Qubryx's technical team needed to move beyond initial GenAI experimentation and build a practical understanding of enterprise-ready AI — strategic planning, governance, security, scalability, and cost alignment, all together.
What edForce did: Ran a focused AWS GenAI session on AWS-native services and the strategic considerations required for enterprise AI initiatives, with emphasis on security, scalability, governance, and cost.
The result: The team moved from isolated experimentation to strategic evaluation, and Qubryx kicked off internal discussions on AWS as a foundation for upcoming AI-driven initiatives and proof-of-concept programs.
"The discussion provided context for evaluating scalability, security, governance, and potential AI use cases at scale."
The problem: Physics Wallah serves over 100 million learners through live classes, recorded content, and AI-powered learning — and needed to plan for high-traffic exam periods alongside future AI initiatives, securely and at scale.
What edForce did: Delivered an AWS edTalk on Agentic AI Foundations covering Auto Scaling, Elastic Load Balancing, and CloudFront for high-traffic scenarios, plus Amazon Bedrock and SageMaker for personalized learning and tutoring use cases.
The result: The session prompted internal discussions to further evaluate AWS as a strategic platform for future AI and cloud transformation initiatives across the platform.
What are enterprise teams exploring?
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