Workflow Intelligence Infrastructure

Human expertise,
machine readable.

The world's most valuable operational knowledge lives in people's heads. We capture it, structure it, and ship it to the AI systems that need it most.

70% of enterprise knowledge
never gets documented
6–12mo to reach basic
operational competency
10K+ baby boomers retiring
daily in the US
DECISION TREE ENCODING — ACTIVE
01 / The Problem
The world's most valuable knowledge has no system of record.
70%
Trapped in Individuals

Critical knowledge lives only in people's heads. Can't be searched. Can't be shared. Can't be systematized.

6–12mo
Impossible to Scale

Training takes months. Sometimes years. Expert-level performance doesn't replicate across teams, locations, or time zones.

10K+
Lost When People Leave

When experienced workers retire or leave, decades of expertise walk out the door. Permanently.

02 / The Solution

From human hands
to intelligent systems.

Three steps. Observe how experts work. Encode what they know. Deploy it at scale. From observation to autonomy.

01

Capture

First-Person Perspective

POV recording of real-world task execution. How experts actually work, decide, and adapt. Observed, not interrupted.

Non-invasive data collection Multi-modal capture Context-aware mapping
02

Encode

Structured Decision Trees

Raw expertise becomes structured AI decision trees. Formal. Executable. A machine-readable map of how experts think.

Automated pattern recognition Hierarchical decision modeling Edge-case handling built in
03

Scale

AI Agent Deployment

Encoded expertise ships through AI agents. Expert-level performance. Unlimited instances. Always on.

Autonomous task execution Real-time adaptation Seamless system integration
03 / The Roadmap
2025
Foundation

One core thesis: human expertise can be captured, structured, and scaled through AI. Designing the architecture for POV capture and decision tree encoding.

2026
Build Phase

POV capture prototype goes live. Recording how experts actually work, decide, and adapt. Raw observation in. Structured decision trees out.

2027
Scale Phase

Encoded expertise ships as autonomous agents. Expert-level output. Unlimited instances. Scaling into manufacturing, logistics, field operations.

2028+
Frontier Phase

Same decision trees. New form factor. Encoded expertise moves into physical robotic systems. Machines that operate with human-level knowledge.

AI agents today.

Robotics tomorrow.

The same encoded expertise, moving from screens into the real world.