North Carolina Navigator

A practical demonstration of a multi-agent, multi-model AI architecture that consolidates knowledge from 20+ North Carolina government websites into a single intelligent agent experience. 🚀

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Share URL

https://agentmadness.ai/entries/north-carolina-navigator

Builder

Daniel Christian

Build Type

Agent Team

Lifecycle

Working prototype

Consensus Score

77.6

Project Link

https://copilotstudio.microsoft.com/environments/1620b6f6-50c5-e638-9695-cae9254ab318/bots/copilots_header_cfcs_NorthCarolina/canvas?__version__=2&enableFileAttachment=true

Demo Link

https://www.youtube.com/watch?v=ygQloMOfv7o

CATEGORIES

ResearchResearchEducation

Go Deeper

Your users shouldn’t have to visit 20+ websites to get one clear answer.

That’s exactly why I built this  Multi-Agent, Multi-Model approach using both GPT and Anthropic models — intentionally selecting the right versions of each to improve reasoning, orchestration, and overall user experience.

For this demonstration, I grounded the solution in knowledge from 20+ official government websites across North Carolina — consolidating complex, distributed public information into a single, intelligent agent experience. Instead of navigating site after site, users interact with one unified system that routes intelligently behind the scenes.

Following are the agents:

- Carolina Environment Agent
- Carolina Business Agent
- Carolina Governance Agent
- Carolina Infrastructure Agent
- Carolina Wellbeing Agent
- Carolina Navigator Agent

This isn’t just about using multiple agents. It’s about designing intentional orchestration, choosing the right models for the right responsibilities, and delivering a seamless user experience through a single conversational interface.

Stack Used

Claude Opus 4.5, GPT-5 Auto, GPT-5 Reasoning & GPT-4.1