Replace guesswork with systems
Turn scattered field notes, texts, spreadsheets, and memory into records people can search, audit, and use.
Gregory Stoltz
Practical AI systems for real-world businesses.
Systems builder. Technology generalist. AI automation architect.
Greg helps small and mid-sized businesses replace paper, memory, scattered messages, and manual coordination with structured workflows, automation, and AI systems that remain understandable and controllable.
He has spent decades building systems that survive real operating conditions, from early Internet infrastructure to mobile field tools and AI-assisted workflows.
inputpaper / memory / field notes
processworkflow / audit trail / sync
outputrecords / summaries / decisions
A public home for working tools
A real home for practical systems.
This domain is more than a personal homepage. It is the public front door for practical tools, experiments, and working systems built around real operational needs.
Some tools live on subdomains. The root site exists to make the domain intentional, accountable, and understandable without exposing private client systems or internal infrastructure.
What the work is about
Automation without losing control
Use AI and scripts to reduce repetitive work while keeping the process understandable.
From field chaos to intelligent workflows
Design tools that survive spotty connectivity, messy handoffs, and real operating conditions.
Explore the work
Start with the practical systems, then follow the philosophy behind them.
Built in the field first
The best systems do not start in conference rooms. They start with a real problem, under real pressure.
The current work begins by solving operational friction directly: field capture, shift notes, quality checks, site knowledge, supply signals, and daily reporting. Once a tool proves useful in live work, it can become a repeatable system. Once the pattern is proven across enough sites, it can become a model for the wider service industry.
That is the path: solve the real problem first, then let the system grow from evidence.
If it does not work in the real world, it does not count.
Working systems matter more than demos, slide decks, and buzzwords. Good tools should make work clearer, not bury it under another layer of software.