-
-
SimpleNet
Inspiration
Modern networks are complex and expensive to operate. Telecommunications and IT teams spend significant time manually checking device health, provisioning configurations, and troubleshooting issues across routers, switches, and servers. We were inspired to simplify this workflow by using AI to automate routine network operations, reduce human effort, and drastically shorten response time.
What it does
SimpleNet is an AI-powered network management system that automates device inspection, monitoring, and reporting. It allows operators to: 1) Query network device health (CPU, interfaces, drops, errors) 2) Automatically analyze device output 3) Generate clear, human-readable operation reports in seconds 4) Reduce manual CLI work and operational overhead What typically takes minutes or hours can now be done in seconds.
How we built it
SimpleNet is built as a multi-agent AI system: The system is written primarily in Python, designed to be modular, extensible, and vendor-aware.
Challenges we ran into
Normalizing outputs across different device platforms , Handling unreliable network responses and transient failures , Designing agent memory without causing stale or excessive context , Balancing automation speed with operational safety
Accomplishments that we're proud of
Built a working multi-agent AI system from scratch , Automated real network health checks end-to-end , Generated NOC-ready operation reports automatically , Designed a system that is scalable and extensible to more device vendors , Get Tested by Engineer (future user)
What we learned
What's next for SimpleNet - AI Network Management System
Long-term memory for historical trend analysis , Proactive alerting and anomaly detection , Self-healing workflows for common network issues , A web dashboard for visualization and operator interaction
Log in or sign up for Devpost to join the conversation.