Building Blocks for Agentic Solutions in your Enterprise

Treat your AI agents like digital employees. Give them identities, permissions, and robust memory to create real business value.

#1about 2 minutes

Moving agentic AI from proof of concept to production

Enterprises struggle to productionize AI agents due to challenges in communicating value, selecting stable technology, and ensuring legal compliance.

#2about 3 minutes

A three-pillar strategy for enterprise AI implementation

A successful enterprise AI strategy requires aligning business outcomes with technology choices and operationalizing development through standardized processes.

#3about 4 minutes

The architectural layers of an enterprise agentic platform

An agentic platform is built on layers including user experience, a runtime, shared memory, and registries for discovering tools and other agents.

#4about 2 minutes

Designing a multi-layered memory strategy for AI agents

A robust memory strategy involves managing session-based context, persistent agent knowledge, and long-term organizational memory to enable hyper-personalization.

#5about 3 minutes

Four patterns for orchestrating multi-agent collaboration

Agents can collaborate through direct connections, as orchestrated tools, within a sequential workflow, or via a decoupled event-driven architecture.

#6about 2 minutes

Implementing human-in-the-loop for agent oversight

Semi-autonomous agents require human-in-the-loop processes for critical decision-making, with interventions designed for the user's specific work context.

#7about 5 minutes

Establishing agent identity for governance and security

Managing agents at scale requires establishing a clear identity for each agent to govern permissions, audit actions, and secure interactions.

#8about 2 minutes

Understanding the maturity levels of agentic AI

The evolution of agentic AI progresses from simple chatbots to semi-autonomous agents with human oversight, which is the current focus for delivering business value.