Challenges
Reducing reliance on specialists for enterprise operations
A premier South African retail conglomerate relied on enterprise platforms for observability, cloud infrastructure, databases, and documentation, but using them required specialized expertise.
Knowledge remained concentrated among experts, creating operational bottlenecks and slowing routine activities. Non-specialists could not access the platform’s capabilities, architecture diagrams took more than five days to produce, and troubleshooting often took more than fifteen days.
The organization needed a natural-language solution to simplify enterprise operations and reduce dependence on specialists.
Solution
Neural AI agents: Empowering non-specialists with agentic AI on AWS
Zensar developed neural AI agents, an enterprise agentic AI platform built on Amazon Bedrock, Model Context Protocol (MCP), and Amazon Q/KIRO CLI. The platform enables users to interact with enterprise systems using natural language while securely accessing business context.
The initial deployment included agents for architecture documentation and observability troubleshooting. The extensible design supports additional enterprise platforms, enabling the organization to expand AI-assisted operations and helping non-specialists perform specialist-level tasks.
Amazon Q/KIRO CLI provides a secure natural-language interface, enabling users to interact with enterprise systems without requiring specialized knowledge.
MCP securely connects large language models to enterprise data, providing the business context required to generate relevant insights and take meaningful action.
Claude, via Amazon Bedrock, delivers reasoning, analysis, and action generation, enabling AI agents to automate documentation creation and platform troubleshooting workflows.
The platform supports future agents for databases, AWS infrastructure, Confluent, and other enterprise systems, enabling scalable AI-assisted operations without a proportional increase in specialist teams.
Solution enablers
Tech stack:
- Agentic AI platform
- MCP
- Amazon Q/KIRO CLI
- Claude
Zensar services:
- Agentic AI platform development
- Enterprise AI integration
- Documentation automation
- Platform operations automation
AWS services:
- Amazon Bedrock
- Amazon Q
Impact
Transforming enterprise operations with agentic AI
Architecture diagrams in minutes, not days
Troubleshooting reduced from days to minutes
Natural-language access for non-specialists
Scalable AI agents across enterprise platforms
Business outcome
The solution reduced documentation and troubleshooting time from days to minutes, enabled non-specialists to perform complex operational tasks, and established a scalable foundation for AI-assisted enterprise operations.
Conclusion
A solution that combines Amazon Bedrock, MCP, and agentic AI can help enterprise operations, reduce reliance on specialists, and create an extensible platform for ongoing AI-driven innovation.