Data everywhere, decisions nowhere
You pay hundreds a month for tools and stare at endless charts. Yet almost none of them tell you the one thing that matters: should you enter this category or not?
The First AI Decision Agent for Amazon Sellers
SATLIS — the AI Agent
for Amazon Sellers
Only SATLIS combines live Rufus conversations, COSMO semantic keywords, neural prediction for high-converting traffic entries, and automated execution through an 8-layer campaign architecture.
5 decision agents × 6 execution skills across the full Amazon operating chain.
Go / Hold / Skip category decisionsCompetitor Research + Outranking PlanDual-validated Search Terms8-layer campaign architectureAI creative assets
This is not a dashboard that hands you raw data and leaves you to figure it out. SATLIS makes the call first, then gives you the next move.
Using SATLIS is like adding an AI operator who understands the full Amazon workflow.
Blue-ocean vs. red-ocean category calls, identifying which competitors are realistic to outrank, generating Outranking Plans, Rufus-powered Search Terms discovery, filtering noise, selecting execution-ready terms, building an 8-layer campaign architecture, and carrying those terms into listing and ad execution all happen inside one agent workflow.
Your job is to press one button.
6 AI skills connected into one operating chain
Each skill makes its own decision and handles the next step. From category entry calls to Sponsored Products execution, SATLIS runs the full chain instead of handing you disconnected tools and asking you to stitch them together.
01
Intent mining
Run live Rufus conversations to capture buyer intent and generate COSMO semantic keywords.
02
Intelligent filtering
Score relevance and conversion probability to remove low-value Search Terms.
03
Opportunity judgment
Keep only the traffic entries worth placing in the listing and funding in Sponsored Products.
04
Listing application
Apply validated terms to Product Title, Bullet Points, and Search Terms.
05
PPC amplification
Scale through an 8-layer Sponsored Products structure.
06
Iteration loop
Review by cycle and keep tightening ACoS while lifting ROAS.
Disconnected tools keep optimizing broken links. SATLIS reconnects the full chain.
Real outcomes driven by AI
Efficiency shifts from real sellers running SATLIS (ratio metrics only).
96.9%
AI-driven order share
8.9x
AI ROAS vs. manual ads
72.1%
Organic order share
Traditional SaaS tools
- Hand you dashboards and expect you to interpret them
- List 10,000 candidate terms and expect you to filter them
- Show competitor dashboards and leave the decision to you
- Export ad reports and leave optimization to the team
SATLIS AI Agent
- Outputs "Category rated A — recommended to enter"
- Filters and delivers execution-ready Search Terms
- Says "This competitor is a realistic target to outrank — here is the plan"
- Predicts which traffic entries are likely to convert before spend goes live
The uncomfortable truth about Amazon seller tools
Why most keyword tools break under Amazon's new AI-driven search environment
Traffic = f(a, b, c, d, e ...)
Traffic drivers keep changing. Reverse-engineering competitor traffic playbooks, even with a 1:1 copy, still leads to very different outcomes. That approach is a follow strategy
SATLIS takes the opposite path: predict the possible answers first, then let Amazon surface the best answer for the moment. That approach is a predict strategy
Search Terms coverage below 1/16
Brand Analytics gives you 42 terms. Your competitors are working with 700+. In the COSMO and Rufus era, traditional tooling misses 94% of real buyer intent.
Ad spend rises while organic stays flat
Manual PPC can run at 56.5% ACoS because budget gets pushed into the wrong traffic entries. You cannot tell in advance which entries will convert and which ones will only burn spend.
Why Amazon sellers are switching to AI Agents
Comparison
Traditional SaaS tools
SATLIS AI Agent
Output format
Traditional SaaS toolsData and charts for you to analyze
SATLIS AI AgentAgent-led conclusions and action packs
Search Terms coverage
Traditional SaaS toolsBrand Analytics level (1x)
SATLIS AI AgentAgent expansion to 16.7x Brand Analytics
Precision filtering
Traditional SaaS toolsManual review
SATLIS AI AgentDual validation: 20K candidates → actionable terms
Category analysis
Traditional SaaS toolsBSR tables
SATLIS AI Agent15-dimension scoring plus a direct recommendation
Competitor intelligence
Traditional SaaS toolsSales estimates
SATLIS AI AgentRealistic-target grading plus an Outranking Plan
PPC optimization
Traditional SaaS toolsManual bid tuning
SATLIS AI AgentNeural prediction plus bid and budget priorities
Campaign architecture
Traditional SaaS toolsFlat campaign structure
SATLIS AI AgentAgent-managed 8-layer allocation
Decision model
Traditional SaaS tools"Here is the data, go figure it out"
SATLIS AI Agent"Here is what to do, and here is why"
5 decision agents, each with a clear job
Each agent makes the call and moves the work forward. Decision first, evidence second, execution next.
Should we enter this category at all?
Category ResearchAgent decision
Outputs a category grade from A to E, then makes a direct go / hold / skip recommendation. The scoring model covers 15 dimensions: demand, competition density, new-product success rate, review barrier, ad pressure, and more.
What traditional tools give you
A spreadsheet full of BSR data. You are still expected to draw the conclusion yourself.
Which competitors are realistic to outrank?
Competitor ResearchAgent decision
Builds a pool of realistic outrank targets with S / A / B grading. Weaknesses are flagged one by one: low ratings, missing A+ Content, no video, weak brand presence, inflated pricing, and more. In open markets it locks the right benchmark model; in crowded markets it pinpoints the first workable gap.
What traditional tools give you
A competitor list sorted by sales volume, with no signal on which ASINs are realistic targets.
How do we outrank this specific competitor?
Outranking PlanAgent decision
Outputs a two-sided Outranking Plan: traffic-side gaps in CTR, Frequently Bought Together, ad placement, and Search Terms; conversion-side gaps in reviews, pricing windows, fulfillment, and content quality. You get the first executable move, not just analysis.
What traditional tools give you
This feature usually does not exist at all.
Are these terms worth spending on?
Keyword RefinerAgent decision
Starts with 20,000 candidate terms and runs dual validation. Gate 1: indexing eligibility. Gate 2: conversion opportunity. Only the Search Terms that pass both gates move into the final execution library, with precision that can reach 16.7x Brand Analytics.
What traditional tools give you
A keyword list sorted by search volume, with no verification, no filtering, and no priority.
What should we fix first in Sponsored Products?
Campaign Architecture EngineAgent decision
Builds an 8-layer campaign architecture instead of one flat campaign. Neural prediction judges whether each traffic entry is likely to convert or likely to burn budget, then sets bid and budget priorities before spend goes live. From 51,309 raw traffic entries, SATLIS isolated 3,273 high-value terms that contributed 72% of total orders.
What traditional tools give you
"Here is your ACoS. Good luck."
The data speaks for itself
Same period, AI-driven vs. manual operations: efficiency comparison (ratio metrics only).
Metric
Manual operations
SATLIS AI Agent
ACoS
Manual operations56.5%
SATLIS AI Agent27.6%↓ 51%
ROAS
Manual operations1.77x
SATLIS AI Agent3.63x↑ 105%
CVR
Manual operations10.7%
SATLIS AI Agent15.4%↑ 44%
CPA
Manual operationsBaseline
SATLIS AI Agent↓ 43%↓ 43%
Organic order share
Manual operationsLow
SATLIS AI Agent72.1%70% of total orders
AI-driven order share
Manual operations—
SATLIS AI Agent96.9%Nearly all AI-driven
Within 30 days, organic daily orders grew 6.4x while ad efficiency doubled at the same time.
Real sellers, real decisions, real growth
"We used SATLIS dual-validated terms for a new ad launch. ROAS reached 5.94 in two weeks, and organic ranking started climbing in week two."
"We moved from manual PPC to the SATLIS 8-layer campaign architecture. Organic order share reached 72.1%, and ACoS dropped from 56% to 27%."
"SATLIS category decisions told us to skip three categories we were about to enter, all graded D or E. The A-rated category is now our best-performing product line."
Four workspaces, one operating base for the agent
Category research, Search Terms, listing execution, ads, and creative all run inside the same system.
Product Research Workspace
From market-entry decisions to competitor outranking strategy.
Learn more
Keywords & Listing Workspace
From 20,000 candidate terms to execution-ready Search Terms and publish-ready listing copy.
Learn more
Ad Optimizer Workspace
From ad chaos to a structured, efficient Sponsored Products setup.
Learn more
AI Image Studio
Listing-grade creative assets in minutes.
Learn more
Frequently asked questions
Straight answers to the questions sellers care about most: profit, conversion, organic share, and growth pace.
What is the real difference between SATLIS and traditional tools?+
Traditional tools output data and charts, and you still have to do the analysis yourself. SATLIS outputs decisions: whether to enter the category, which competitors to prioritize, which Search Terms deserve spend, and what to fix first in Sponsored Products. Every module gives you an execution-ready decision, not a pile of numbers you still have to interpret.
What does "decision-first" mean? Is the AI deciding for me?+
SATLIS does not take the final call away from you. It gives you a recommendation backed by an evidence chain. Category Research shows the open-market or crowded-market call with 15 scoring dimensions. Competitor Research shows which competitors are realistic to outrank and exactly where the gaps are. The decision is still yours, but you no longer spend hours turning raw data into a recommendation.
How does the dual Search Terms validation work?+
Gate 1 checks whether Amazon indexes your ASIN for that Search Term. Gate 2 checks whether the term has real conversion potential for your ASIN. Only terms that pass both gates move into the final Search Terms library, which keeps ad budget away from dead-end traffic entries.
Is this only for new launches, or does it work for mature ASINs too?+
Both. The new-launch path starts with category decisions, competitor positioning, and Search Terms filtering before the listing and ad launch. The mature-ASIN path uses the 8-layer campaign architecture and prediction logic to rebuild existing Sponsored Products, reduce ACoS, and grow organic order share at the same time.
Which Amazon marketplaces does SATLIS support?+
SATLIS supports all Amazon marketplaces. Its value is especially clear for sellers in non-English marketplaces such as Germany, France, Italy, Spain, and Japan. In those markets, the biggest challenge is not getting listed. It is finding keywords that can actually compete. Most keyword tools handle non-English marketplaces in a very blunt way: they start with English keywords and then run them through Google Translate. The wording may look acceptable on the surface, but it often does not match how shoppers actually search on Amazon in each local marketplace. The result is less precise traffic, weaker ad efficiency, and lower conversion rates. SATLIS solves that exact problem. It can generate core Cosmo keywords tailored directly to Amazon's non-English marketplaces, rather than relying on English source terms or literal machine translation. The output is much closer to Amazon's search logic and local shopper behavior. So SATLIS is not just solving a multilingual problem. It is solving the real traffic and conversion problem in non-English Amazon marketplaces.
Where should I start if I am using SATLIS for the first time?+
Start with Category Research or Competitor Research to get your first operating recommendation. Then connect Search Terms, listing, and Sponsored Products into one execution loop. The best rollout is to run one ASIN group through the full cycle first, then expand to more categories and accounts.
Stop optimizing blindly. Start with the decision.
Your competitors are still guessing from dashboards. You can start with the decision and move straight into execution.