Core business
Identify the work that creates revenue, protects margin, or improves the customer promise, then make that work sharper.
AI systems specialist for operators
Marc Pelberg
I help operators decide what work should exist, what should be automated, and where AI can act with enough trust to become a real business system.
The paradigm has completely shifted. AI is not just a faster way to do familiar work. When knowledge work can be handled by the smartest tool in history, the question becomes: what is core to the business, what is secondary, what should be automated, what should stay human, and where must trust be built before the system acts?
Built across operating companies
Decision framework
From work people do to systems businesses can trust.
Secondary work
Separate the tasks that drain time or money: cleanup, matching, publishing, reconciliation, research, reporting, and follow-up.
Automation boundary
Decide what needs a UI, what can run quietly in the background, and what should only recommend until confidence is high.
Trust before action
Build review, audit trails, thresholds, and escalation into the system so AI earns more autonomy over time.
Why this perspective is different
Operator first, builder second, AI only where it earns trust.
Public profiles connect my work to RealArb, SkuTrue, Dragon Apparel, e-commerce operations, retail automation, and AI-enabled product data. I have also consulted with various companies and worked from owner/operator roles across Midas Holiday Lighting, Eli & Associates, Inc., and Artex Knitting Mills. That mix matters because useful AI is not decoration. It closes the gap between a business process, a decision, and a result that can be trusted.
- RealArb
- Marketplace and arbitrage operating experience across international e-commerce, where small decisions compound into margin.
- SkuTrue
- AI-oriented retail operations and product-listing automation for messy catalog work that should not stay manual forever.
- Risk practice
- Private pilot, EMT, and state/regional paragliding distance record holder across New Jersey, Pennsylvania, New York, Michoacan, and Puebla.
- Consulting and ownership
- Consulted with various companies and brought owner-level operating context from Midas Holiday Lighting, Eli & Associates, Inc., and Artex Knitting Mills.
Examples from the field
The pattern is deciding what work deserves human attention.
Catalog intelligence
Public podcast material describes SkuTrue as using web scraping and AI to move product data across Amazon, eBay, and Walmart. The business question is what can run in the background and what needs review before it touches revenue.
Marketplace operations
RealArb support docs, Zayda profiles, and Dragon Apparel retail work all point to the same operating problem: listings, inventory, orders, and pricing need systems that know when to act and when to ask.
Judgment under pressure
Private pilot, EMT, Monarca competition experience, and paragliding records in New Jersey, Pennsylvania, New York, Michoacan, and Puebla all reinforce the same habit: read the system, respect the downside, and make clean decisions with incomplete information.
How engagements work
Start with the work, then decide what deserves software.
01
Map core vs secondary
We separate revenue work, cost-reduction work, and the repetitive tasks that only exist because no system is doing them yet.
02
Choose the interface
Some work needs a dashboard, some needs a quiet background agent, and some should only draft or recommend until the trust level is right.
03
Raise autonomy carefully
The system earns more freedom only when the data, review trail, accuracy, and business outcome prove it should act without constant human help.
Reach out
Have an ugly workflow that should be smarter?
Send the process, the pain, and what a good outcome would look like. I will help you decide whether it should stay human, become software, or run quietly with the right trust checks.