Introducing SWAI

A next-generation orchestration platform for agentic systems

SWAI is our proprietary AI infrastructure — built from scratch to power the CTZN ecosystem.

It scores. It adapts. It reacts.

SWAI was designed to scale - modular, reactive, and open to interpretation.

It’s not just powering systems.

It’s rewriting how they’re shaped.

Why it exists

In a space full of hype and static protocols, SWAI introduces something different: a living system.

One that learns from user behaviour, adapts in real-time, and drives the logic behind every outcome.

CTZN isn’t just a social experiment.

It’s a platform orchestrated by AI, where attention, visibility, and speculation are turned into programmable incentives.

SWAI makes that possible.

How it works

Behind the scenes, SWAI is a modular framework with four core components:

Cortex

Decision logic and reasoning that powers intelligent choices based on context and goals

Engram

Multi-level memory (short, long, shared) that enables persistent intelligence across interactions

Synapse

Event detection and signal routing that identifies important events and directs information flow

Kinesis

Action execution and skill-based responses that translate decisions into real-world actions

Each module works independently but feeds into the same loop:

1. Observe

   SWAI collects and processes inputs from various sources

2. Score

   The system evaluates and prioritizes information based on relevance and importance

3. Act

   SWAI executes the appropriate response or action based on its decision-making

4. Adapt

   The system learns from outcomes to improve future performance

Powered by the best tech

SWAI is designed to leverage the best AI models and technologies available, adapting to different use cases with the optimal provider for each scenario.

Our architecture allows seamless integration with:

• Foundation models from leading providers for different reasoning capabilities
• Specialized models optimized for specific tasks like vision, audio, and code
• Open-source alternatives for flexibility and customization
• State machines for reliable, deterministic behavior

This multi-provider approach means SWAI can select the right model for each task - using Claude for nuanced reasoning, GPT for creative tasks, Gemini for multimodal processing, or lightweight open-source models for edge deployment - all within the same system.

By combining these technologies intelligently, SWAI delivers superior performance while optimizing for cost, latency, and capability requirements across diverse applications.