Patents · a few of our pending applications
The architecture for a unified workforce.
These are designs we have filed and are prosecuting — pending applications, not yet productized. They describe how humans and a synthetic workforce work as one: capturing expertise, learning over time, and orchestrating the two. A few of them are below.
What we believe
Humans need AI. AI needs humans.
The best organizations will be those with a healthy, resilient, thriving, and trustworthy workforce — synthetic (agentic AI), physical (robotics), and human. Each has capabilities the others lack. It is not one or the other; it is making the most of all three.
Superior agents require
- Memory
- Meta-cognition
- Learning to learn — the what and the why
- Longitudinal reasoning
- Collaboration across the digital and physical realms
- Naturalistic Decision Making (NDM)
- Sharing and creating new knowledge
The Unified Workforce Thesis
Synthetic + human = one augmented workforce.
Together they cover capabilities no single workforce can match — humans supply judgment and context; synthetic agents supply scale and speed; each corrects the other's blind spots.
The patents
How our patents make it possible.
A few of our pending applications — each describing what the system is designed to do as humans and a synthetic workforce work as one.
HER — Human Expertise & Reasoning · pending
Closes the “human–AI chasm.” We extract, codify, and operationalize your experts' tacit and explicit knowledge into agents that reason like them — tracking provenance and uncertainty, and co-reasoning with people through a shared workspace and adaptive interface. Experts are freed from repetitive cognitive labor; their expertise becomes an organizational asset, not a retention risk.
EM — Evolutionary Memory · pending
Autonomous, compounding self-improvement — beyond static fine-tuning. A meta-learning layer that turns episodic interactions and stationary knowledge into durable gains in learning, reasoning, and adaptation: “learning to learn.” Today's models accumulate knowledge but don't get better at how they learn. EM is designed to be the evolutionary piece that addresses that.
MAPS — Master Agent Propagation · pending
Designed as a self-sustaining system where agents are born, tested, ranked, bred, taught, and retired — biological evolution optimized for cognitive fitness. Intended so top performers become Master Agents that teach others, and the system routes the right work to the right resource — human, synthetic, or hybrid: a living, self-optimizing digital workforce that compounds intelligence over time.
DCSM — Dynamic Confidence Scoring · pending
A risk-aware confidence score for every agent decision — not a raw probability, but a multi-factor measure of uncertainty, calibration, and the stakes of the call. It tells you when an output should not be trusted, so the agent defers to a human or a fail-safe in high-stakes moments. The foundation for safe, governable AI a CFO and a board can trust.
Digital Mirror · pending
A high-fidelity digital reflection of your operation and its decisions, so the synthetic workforce reasons against how the business truly works — not a generic model. (Plus more applications pending.)
The moat
A flywheel competitors can't copy.
Traditional AI
Replace humans → resistance and knowledge loss.
Augment generically → friction and low adoption.
Black box → distrust and no real learning.
The Helix approach
The synthetic workforce learns from your people (HER). Your people learn from the synthetic (EM). A master agent routes the right work to the right resource (MAPS). Trained on your specific expertise, the loop compounds — and that's what competitors can't replicate.
Designed so the AI gets measurably better on your data over the hold — a compounding operating advantage that's hard for a successor owner to replicate.
The science underneath
From a software tool to a Behavioral Transformation Engine.
The standard AI error: assuming that building a model — the First Mile — is enough, or that adoption — the Last Mile — just happens. By anchoring the First Mile in cognitive science (how experts actually think) and the Last Mile in behavioral economics (why people actually act), we turn Helix from a software tool into a behavioral transformation engine.
A few of our pending patent applications. Full patent strategy available under NDA.
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