AI and Agentic Infrastructure

This report examines the emergence of a new AI technology stack built to support the deployment of agentic AI at scale. We explore how organizations are adapting their software infrastructure to handle AI workloads and building the foundational platforms that enable sophisticated agentic systems.

In the report, we analyze the evolution from simple "models plus prompts" toward complex, multi-step agents and the emergence of specialized infrastructure designed to make agents production-ready, reliable and trustworthy.

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Agentic Infrastructure Market Map - Compact View

Agentic Infrastructure Market Map

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AI Assurance

Agent Fabric

Model Infrastructure

ModelOps

Foundation Models

Note: The information herein is illustrative and subject to change. The information herein references five (5) Georgian portfolio companies (Clerk, Coder, Island, Render & SurrealDB) and represent a subset of the firm's prior investments. The referenced portfolio companies may not be representative of the firm's investment experience or performance as whole. Please contact Georgian for more information on the firm's investments, including its firm's engagements with portfolio companies and prospective portfolio companies. The information may contain logos of third-party companies. These logos are the trademarked property of the respective companies and do not suggest or imply any affiliation, endorsement, or sponsorship of Georgian or any fund, vehicle or product.

Report Highlights

1. The New AI Technology Stack

The software infrastructure market's shift to support AI and agentic workloads is creating opportunities for new entrants to disrupt various parts of the market. We explore how this transformation spans both existing categories like databases and data transformation, as well as new AI-specific categories including foundation models, model infrastructure and agentic infrastructure.

2. Foundation Models: The Core Intelligence

From large language models (LLMs) to large reasoning models (LRMs), multimodal models, voice models and emerging world models, we examine how foundation models serve as the "brain" powering AI systems.

3. The Agent Fabric Layer

We outline the building blocks developers are likely to need to move agents from prototype to production, including orchestration and guardrails, durable execution, agent memory, tool discovery through Model Context Protocol (MCP), authentication and authorization, human-in-the-loop UX and secure sandboxes for testing.

4. Building Trust Through AI Assurance

As agents become more autonomous, organizations will need to have confidence that AI systems are performing as intended. We explore how evaluations, simulations, red teaming and observability tools help development teams detect degradation, prevent failures and maintain reliability in production environments.

5. Agentic Infrastructure Market Map

Our market map charts the emerging landscape of AI and agentic infrastructure across foundation models, model infrastructure, agent fabric and AI assurance, highlighting both established players and emerging startups that are changing how organizations build and deploy intelligent systems.

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