SyncOrch Ecosystem

Welcome to the SyncOrch Ecosystem. This is a story about how a cohesive platform resulted from a series of projects, each one solving a critical strategic problem. It was only in hindsight that I realized I wasn't building separate projects; I was building a complete AI infrastructure, layer by layer. Now this formalized layered system serves as a blueprint for how I approach strategic orchestration.

The SyncOrch Ecosystem: An Orchestrated Foundation

Orchestration layer: SyncOrch

Interface layer: Jorge AI

Memory layer: ThreadAnchor

Application layer: PSN-AI

Reasoning model: Tension OS, HowThink

Problem layer: PSN

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Overview

A Journey Through AI-Driven Projects

From healthcare access to Autonomous Science

Explore Layers

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SyncOrch: The Orchestration Layer

The next frontier in AI is not merely optimizing human-defined tasks, but enabling AI to autonomously define, pursue, and validate scientific discoveries. SyncOrch is the foundational orchestration layer for this vision of Autonomous Science.

We envision SyncOrch as the "Mission Control" for AI, where Dynamic AI Teams—fluid, self-organizing collectives of specialized AI agents—are deployed like "astronauts" into the vast, unknown frontiers of scientific inquiry.

Mission: To empower AI to autonomously define, pursue, and validate scientific discoveries, fundamentally accelerating our understanding of the universe and even AI's own evolution.

Core Concepts: SyncOrch provides the critical infrastructure for Goal-Oriented Emergence. It enables AI teams to assemble and dissolve on demand, exhibit fluid specialization, and self-diagnose and optimize their own performance.

The Problem It Solves: It moves beyond the current paradigm of "directed intelligence" and solves the problem of how to enable AI to become an autonomous agent in the discovery of the universe. This is the intellectual and technical leap from a collection of powerful, yet isolated, intelligences to a collective, emergent intelligence.

Go to SyncOrch

PSN: The Problem Layer

Before there was an AI solution, there was a real-world problem. The original Patient Support Network (PSN) was a human-driven initiative born out of a personal experience with fragmented and difficult healthcare navigation. This project identified the critical tensions that exist between patients, institutions, and providers in a complex healthcare system. PSN is the foundational "problem layer" that motivated the creation of the entire SyncOrch Ecosystem.

Read Problem Statement

View Original Prototype

PSN-AI: The Application Layer

The PSN-AI (Patient Support Network AI) project serves as the tangible proof-of-concept for the entire SyncOrch Ecosystem. It is the flagship pilot that demonstrates the power of our orchestration layer in a critical, human-centric domain: healthcare navigation.

Conceived as a "Global Healthcare GPS," PSN-AI is designed to tackle the problem of strategic fragmentation within patient care. It aims to revolutionize how patients navigate complex care pathways by:

Orchestrating disparate information: It brings together a patient's unique needs, medical history, and available care options into a single, cohesive view.

Applying the Tension OS methodology: It balances the needs of patients, institutions, and providers to generate an optimal care pathway.

Delivering a tailored experience: It guides patients and their families like a "healthcare GPS" to the best possible treatment options.

This project is not a standalone application; it is the Application Layer that validates the foundational strategic vision of SyncOrch.

View the PSN-AI Prototype

Read the Explainer

Tension OS: The Reasoning Engine.

I codified a methodology I use internally—identifying tensions in decision-making—and built Tension OS, a GPT-powered cognitive framework to help others surface and resolve strategic contradictions. This is the intellectual core of the SyncOrch Ecosystem, a repeatable system for navigating paradoxes like Innovation vs. Risk Management and Autonomy vs. Governance.

Read the Methodology

ThreadAnchor: The Memory System.

I was moving fast—and losing track of insights across chat sessions. ThreadAnchor is the long-term memory of the ecosystem. It's a memory layer designed to anchor, retrieve, and thread ideas over time, ensuring that every insight is captured and accessible for future strategic analysis.

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View Memory Layer Artifact

Jorge AI: Human-facing Interface

This is the human-facing interface of the ecosystem. Originally conceived as a "self interface," Jorge AI is a digital twin that experiments with how to translate complex technical processes into a seamless, conversational experience for the user. It is the human-AI touchpoint that makes the entire system accessible and intuitive. It is manifested as “Agent P” on the PSN-AI prototype.

View Interface Layer Artifact

HowThink: Reasoning Identities

Based on the insights from Jorge AI and the Tension OS methodology, I developed the conceptual framework for HowThink. This layer is designed to capture, formalize, and replicate the unique reasoning identities users can assign to multi-agent systems. It is the identity layer that ensures the ecosystem's output remains consistent, transparent, and aligned with its strategic mission.

View Reasoning Layer Artifact

PSN

Current Focus: Applying the SyncOrch Ecosystem to PSN-AI

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Patient Support Network (PSN) is evolving. PSN-AI is the intelligence layer I've recently added using SyncOrch's AI orchestration approach. It organizes patient stories into a map of care pathways that guide patients like a "healthcare GPS."

View the PSN-AI Prototype

Read the Explainer