Kapil Gupta
Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow
#1about 3 minutes
Overcoming enterprise AI silos with a unified strategy
Enterprises can move from scattered AI projects to a unified strategy by mapping initiatives, identifying common patterns, and using design workshops to align teams.
#2about 1 minute
Adopting a platform as a product mindset
A "platform as a product" approach balances central governance with project flexibility, accelerating development by providing reusable components and best practices.
#3about 4 minutes
Architecture of a unified data and GenAI platform
The platform architecture consists of a cloud-agnostic infrastructure, a foundational data and AI workbench, and a top-level GenAI layer for model evaluation and serving.
#4about 3 minutes
Building a self-service data and AI workbench
A self-service workbench accelerates projects by providing pre-configured environments, experimentation tools, annotation toolsets, and automated deployments.
#5about 3 minutes
Integrating GenAI components and execution strategy
The GenAI layer integrates diverse models with robust observability and security, built by leveraging and consolidating existing internal platforms to accelerate development.
#6about 4 minutes
A phased approach to building the AI platform
Implementing the platform involves a phased MVP approach, starting with foundational blueprints and environments, followed by use case development and system hardening.
#7about 4 minutes
Platform offerings for no-code to pro-code users
The platform serves all user types by offering model hosting, legacy system connectors, and an agent kit to support everyone from no-code business users to pro-code developers.
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