Amazon repricer for private-label brands
An Amazon repricer that prices for profit, not buy box panic.
Oracle learns your demand curve, protects your margin floor, and explains every price recommendation before it ships. Built for brand owners, not race-to-the-bottom resellers.
Launch path
Read-only pricing review first
AI pricing employee
Oracle reviews price, demand, margin, inventory, and PPC context before recommending a change. You see the rationale before anything touches Seller Central.
Starts with
Review
No live price changes during the first pass.
Best fit
Owned brand
Private-label sellers controlling the listing.
Optimizes
Profit
Demand curve and margin, not unit volume alone.
Guardrail
Floors
Hard margin and price limits on every move.
Amazon repricer
Fit filter
Oracle is not for every Amazon seller.
The highest ROI clicks are private-label operators with enough price elasticity and margin room for pricing decisions to matter.
Good fit
- You own the brand, control the listing, and can test prices without fighting other sellers on the same ASIN.
- You have margin floors, COGS, inventory constraints, and ad performance that should influence pricing.
- You want pricing recommendations that explain the demand signal before they go live.
Not a fit
- You are a reseller trying to chase the buy box minute by minute.
- You need the cheapest rule-based repricer for wholesale or arbitrage.
- You cannot safely test prices because the catalog has no margin room.
Why teams switch
Most repricers teach brands to think like resellers.
Buy box repricing is useful when you sell the same listing as everyone else. Private-label brands need a different decision: which price maximizes profit for the catalog you own.
Race-to-bottom logic destroys brand margin.
Matching competitor moves can grow units while shrinking dollars. Oracle treats margin floor as a constraint, not a suggestion.
Manual pricing moves too slowly.
A spreadsheet review cannot react to demand shifts, stock risk, PPC changes, or seasonal pressure at the speed your catalog needs.
Promotions hide real elasticity.
Static promo calendars train teams to discount by habit. Oracle separates temporary lifts from real demand curve learning.
Meet Oracle
Hire Oracle, the AI pricing employee.
Oracle gives private-label brands a controlled pricing loop: learn demand, protect margin, explain the decision, and only then change price.
01
Demand-curve learning by ASIN.
Oracle studies your actual sales history and price response instead of applying generic marketplace averages.
02
Margin floors are hard constraints.
She refuses price moves that violate the limits you set and explains why the recommendation was blocked.
03
Pricing and PPC coordinate.
A price change can make ads more or less profitable. Oracle works with Marko so bids and price do not fight each other.
04
Observe mode before autonomy.
Oracle shows the prices she would set and the projected profit impact before any write access is granted.
Application handoff
The application qualifies pricing economics before the call.
A repricer click only matters if the catalog has enough owned-brand control and margin room. The application filters for that before anyone wastes a sales cycle.
Submit the short application.
The form asks for brand, contact, revenue band, ASIN count, and the employee you want reviewed. Oracle is preselected here.
We check catalog fit within 24 hours.
If you are a reseller or do not have enough pricing control, we say so. If it is a fit, we schedule the pricing review.
Oracle starts read-only.
You see proposed price changes, margin guardrails, and rationale before Seller Central write access is granted.
$82M+
profit unlocked for Amazon brands
“Profasee found the price points we never would have tested manually. The lift on our hero SKU paid for the platform in the first month.”
David Schomer
Founder|Espresso Vivace, premium coffee brand
Apply for access
Put Oracle on your team.
Tell us about your brand and Oracle will run a read-only analysis on your account before changing anything.
Common questions
- Who is Oracle a fit for?
- Private-label Amazon brands that own their listings, have enough sales history to learn from, and care more about profit than chasing every unit.
- How is Oracle different from Aura, BQool, Seller Snap, or Informed?
- Those tools are strongest for buy box competition and rule-based repricing. Oracle is built for owned-brand pricing, margin floors, demand learning, and explainable recommendations.
- Will Oracle drop prices below cost?
- No. You set margin floors and price limits. Oracle treats them as hard constraints.
- Do you need write access on day one?
- No. Oracle starts read-only and shows the price changes she would make before you grant write access.
- What happens after I apply?
- We review the application, confirm catalog fit, then connect for a read-only pricing review if Oracle can likely create profit lift.