Adaptive Expert Architecture

🌍 Inspiration

The current generation of AI systems relies on powerful but static, general-purpose models.

As shown in our challenge slides, one model is forced to do everything, performance varies across domains, and improvement requires manual redesign

We were inspired by one core question:

Instead of building one bigger model, why don’t we build a system that learns how to use the right model?

Research consistently shows:

Specialized models outperform generic ones in targeted domains.

Fine-tuning small models can rival much larger systems.

Domain adaptation improves measurable benchmark performance.

This inspired us to rethink AI architecture — not scaling parameters, but scaling intelligence.

🧠 What We Built

a framework to create and orchestrate a swarm of self-improving small language models (SLMs)

Our system consists of:

A Root Agent (Router)

Multiple Specialist Agents

A marketplace of fine-tuned SLMs

A continuous feedback loop

Built With

• adk
• langgraph
• python
• slm