Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow

Is your GenAI strategy just about models, or are you building the scalable ecosystem required for tomorrow's enterprise?

#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.