RONOR

Inspiration

Enterprise AI is fragmented — teams juggle multiple providers, face vendor lock-in, and lack transparency on model decisions and costs. We built RONOR to solve this with a sovereign, provider-neutral runtime.

What it does

RONOR orchestrates 9+ AI models across 7 operational planes: Gateway, Context, Model Fabric, Agent Runtime, Execution, Assurance, and Economics. It routes every request to the optimal model based on capability, cost, and compliance — with full evidence trails.

How we built it

TypeScript/Node.js backend with OpenAI Codex as the primary development partner and GPT-5.6 as the core reasoning engine. The EMS formula (Efficiency x Model-fit x Sovereignty) governs all routing decisions.

Challenges we ran into

Achieving true provider neutrality while maintaining sub-200ms routing latency. Designing the Assurance plane to validate outputs without adding prohibitive overhead.

What we learned

AI orchestration is not just about calling APIs — it requires economic modeling, sovereignty constraints, and evidence governance at every layer.

What's next

Production deployment for enterprise clients, additional model integrations, and open-sourcing the routing engine.

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for RONOR

Production deployment for enterprise clients, additional model integrations, and open-sourcing the routing engine

Built With

• codex
• gpt5.6
• node.js
• openai
• typescript