MatrixSwarm is designed to integrate seamlessly with AI — not just as a consumer of inference, but as an autonomous executor of intelligent reflex.
🧠 What Kind of AI?
- ✅ GPT (OpenAI, Local, Open Source)
- ✅ Embedding-based enrichment (vector similarity, context ranking)
- ✅ Prompt templating for alerts, summaries, or mission decisions
📡 Use Case: Triage Alerts
Example: an agent receives a stream of critical `.msg` files. An attached AI factory enriches them before relay:
This summary could be injected into Telegram or Discord messages, or routed differently based on score.
📁 Factory-Injected AI Behavior
💡 Why This Works
- Modular: GPT logic is optional, hot-swapped, and self-contained
- File-native: All AI decisions are attached to payloads — not hidden in middleware
- Scalable: Can enrich logs, write summaries, or analyze swarm behavior
AI inside MatrixSwarm isn’t just reactive. It’s strategic. You can score, reroute, and even spawn agents based on GPT decisions.
🔗 Future Possibilities
- Autonomous mission assignment via language agents
- Structured message parsing using GPT for DSL commands
- Agent-to-agent coordination via AI-interpreted trees
AI doesn’t run the Swarm. It enables it to reason between cycles. Think of it as reflex extension — or tactical foresight.