Source
From retrieval to agents: 5 takeaways on production architecture for AI agents
Enterprises are shifting from search-driven AI to agentic AI, which requires a transition toward production architecture focused on context engineering for reliability.
Why it matters
Low trust in factual accuracy currently prevents over 50% of companies from moving their agentic AI trials into full production.
The details
- Only 12% of companies are always confident in their discovery tools' factual accuracy.
- Model Context Protocol (MCP) is the standard for connecting agents to enterprise data.
- Context rot occurs when irrelevant information exhausts a model's attention budget, reducing accuracy.
Show entities and relationshipsHide entities and relationships
In this article
Topics
Technologies
Companies
Organizations
People
Key connections
Amy Machado works at IDC
Amy Machado is a senior research manager at IDC.
Elastic is related to Agentic AI
Elastic provides search, context engineering, and observability platforms for agentic AI production architectures.
Elastic commissioned IDC to conduct an independent business value study on its enterprise customers.
IDC is related to Agentic AI
IDC conducts market research on enterprise trust and adoption barriers in agentic AI deployments.
Elastic is related to Context Engineering
Elastic provides search and retrieval-based context engineering to improve agent accuracy and reduce token costs.
Elastic uses Hybrid Retrieval
Elastic combines hybrid retrieval with reranking and secure access controls for agentic AI workloads.
Show 4 more connectionsShow fewer connections
Elastic is related to Vector Database
Elastic offers a unified architecture to avoid the application sprawl caused by stitching together separate vector databases.
Elastic uses Model Context Protocol
Elastic connects agents to enterprise data and tools using Model Context Protocol.
Elastic uses Agent2Agent
Elastic supports Agent2Agent protocols to enable multi-agent collaboration across enterprise systems.
Context Engineering is related to Agentic AI
Context engineering serves as the foundational discipline to prevent context rot and ensure accuracy in agentic AI.
Related events
Webinar on Production Architecture and Context Engineering for AI Agents
Get the weekly recap
The stories like this one, picked and explained — once a week, straight to your inbox.