AI infrastructure built for how commerce teams actually work.

Shopped replaces the patchwork of email, spreadsheets, portals, SharePoint, and legacy UIs with a governed workspace where AI agents do the heavy lifting and every action is auditable.

Your infrastructure, complete privacy. Zero LLM data retention · Private cluster · Enterprise governance

ACME Team Workspace

Detail

Conversations
@justin
@susan
@Media AgentMedia
@GEO AgentGEO
@Reviews AgentReviews
@Onboarding AgentStart
Workspace
Reports
Instacart Campaigns
Share of Voice Audit
ROI Opportunities
Buyers
Mark Ellison (Kroger)
Dana Choi (Walmart)
Media Agent
GEO Agent
Amazon Reviews
🚀 Get Started
📊 Instacart Campaigns
📊 Share of Voice Audit
📊 ROI Opportunities
+ Add

Select an agent to get started

Inbox
Review Instacart campaigns
Send monthly performance summary
📊 Instacart Campaigns
📄 DoorDash Attribution
Review pricing alert
Prep buyer meeting brief
Inbox
Review share of voice audit for
Review new ROI opportunities
📊 Share of Voice Audit
📊 ROI Opportunities
Prep audit kickoff brief
Add site analytics to data checklist
Inbox (Recently Completed Work)
Respond to concerning reviews
Map review themes to content arcs
📊 Amazon Sentiment — last 30 days
📄 Brand health snapshot
Run sentiment refresh

Get Started

Tell us a bit about your team so we can set up your workspace.

What are you focused on?
Retail Media
Availability
Promo
Launch
Sales
Ecommerce

Instacart Campaigns

January 2026 · Generated by Media Management Agent · Last updated: today

Campaigns 3 active

CampaignStrategyROASAction
Flea & Tick Topical — Category CaptureConquesting4.2×
Brand — Core TermsBranded8.7×
Grain-Free Kibble 12lb — Promo SupportVelocity1.1×

Estimated Velocity Impact

Net Unit Change
+140 /week
Weekly Savings
$1,240
Blended ROAS
+0.6×

Data Sources

Instacart Ads
POS
promo planning.xlsx

Share of Voice Audit — Cycling Category

Retail AI Search · 30-day cycle · Recommendations only · GEO Agent
Last updated: today

🎯 Source info access 💰 AI cost budget transparency

Summary

Visibility across AI-powered retail search results is moderate but uneven. Branded queries perform well, while high-volume category terms like "mountain bikes under 1000" and "electric bike accessories" show significant opportunity gaps. This audit establishes a 30-day baseline and identifies the highest-ROI actions for the next phase.

Share of Voice Query-volume weighted

QueryVolumeVisibilityOpportunity
mountain bikes under 100018,400 /mo28%High
electric bike accessories12,100 /mo15%High
bike helmets22,600 /mo34%High
kids bikes15,800 /mo21%High
road bike tires9,200 /mo52%Medium

Visibility Benchmark 30-day delta

TermBaselineCurrentΔ
mountain bikes under 100024%28%+4%
electric bike accessories19%15%−4%
bike helmets31%34%+3%
kids bikes22%21%−1%
road bike tires48%52%+4%

Data Sources

Retail Search Query Reports
Site Analytics
AI Results API

Audit Phase Context

Recommendations only. This audit cycle produces visibility benchmarks and prioritized opportunities. Full engagement (closed-loop optimization with automated content updates and A/B testing) is available as a next phase upon team approval.

AI Cost

Estimated audit cycle cost:$284View audit cost breakdown →

ROI Opportunities — Cycling Category

Retail AI Search · Ranked by estimated visibility impact · GEO Agent
Last updated: today

Summary

Five high-impact opportunities identified from the current share of voice audit. These are ranked by estimated visibility gain weighted against implementation effort. All recommendations are actionable within the current 30-day cycle and require no additional data access.

Highest ROI Opportunities Ranked

  • Optimize PDP content for "mountain bikes under 1000" — largest volume gap
  • Add structured data (specs, compatibility) to "electric bike accessories" listings
  • Create retailer-specific Q&A content for "bike helmets" category terms
  • Improve review velocity on underperforming "kids bikes" SKUs
  • Align brand story content with AI answer-box format for "road bike tires"

Estimated Impact

Avg. Visibility Gain
+8–12%
Terms Affected
5
Implementation
2–3 wks

Audit Phase Context

Recommendations only. This audit cycle produces visibility benchmarks and prioritized opportunities. Full engagement (closed-loop optimization with automated content updates and A/B testing) is available as a next phase upon team approval.

Data Sources

Retail Search Query Reports
Site Analytics
AI Results API
Select an agent to see context here
Media Agent
3 active Instacart campaigns reviewed. Category Capture has headroom to scale (ROAS 4.2×), and Grain-Free Kibble 12lb Promo should be paused — CPC exceeded break-even during the promo window.
Ask a follow-up…
Instacart Campaigns
You're viewing the January Instacart campaigns report. Scale Category Capture (+15% CPC) and pause Grain-Free Kibble 12lb promo spend.
Ask a follow-up…
GEO Agent
Audit scope is set: 30-day cycle, recommendations only. Query-volume-weighted opportunity list ready for review.
Ask a follow-up…
Share of Voice Audit
Cycling category visibility audit. Top priority: "bike helmets" at 22.6K monthly queries with 34% visibility.
Ask a follow-up…
ROI Opportunities
Five opportunities ranked by visibility gain. Biggest win: PDP optimization for "mountain bikes under 1000."
Ask a follow-up…
Amazon Reviews Agent
12 concerning reviews identified in the last 30 days. Product health is 72, down 4 points.
Ask a follow-up…
Onboarding
Please enter your information to get started.
Ask a follow-up…

Commerce teams are fast. Their tooling isn't.

Three things keep tripping up even great teams.

Data lives in silos

POS, retail media, supply chain, trade promo—all in separate tools with separate logins and separate truths.

Teams are split across functions

Sales sees one thing, marketing another, ecommerce a third. Everyone has context—no one has the full picture at once.

Decisions stall

Ownership is unclear, approvals are informal, and by the time something gets done the window has closed.

AI can now do real work. The missing piece is teamwork.

Planning tools got smarter. Agents can pull data, run analyses, and draft recommendations faster than any analyst. That part's here.

What's still missing is the multiplayer layer—permissions, handoffs, shared context, and approval gates that let humans and agents work together without anyone going rogue.

Shopped is that layer.

Three steps. One shared operating surface.

1

Connect

Plug in your systems and files—retail media platforms, POS feeds, inventory data, spreadsheets, trade calendars. Shopped normalizes them into a shared context your whole team can reference.

2

Decide

Agents surface what matters, propose actions, explain their reasoning, and cite the data. Your team reviews, adjusts, and picks the path forward—together, with full visibility.

3

Execute

Assign owners, set approval gates, fire automations, and track outcomes. Every action has a name on it, an audit trail behind it, and a result you can measure.

Agent Conversation
AI
CPA on Grain-Free Kibble 12lb exceeded target by 2.4× for the last 52 hours. In-store velocity is flat and inventory is healthy. Recommend pausing this campaign and reallocating $1,240/week to Category Capture.
2 min ago
JT
Makes sense. Go ahead — pause it and shift the budget.
1 min ago
AI
Done — campaign paused, budget reallocated
just now

Real decisions your team faces every week.

Each one used to take days of emails and spreadsheets. Now it's a conversation with your agent.

Retail Media

Ad spend is burning with no lift

Detect wastePause campaignNotify teamReallocate
Availability

Key SKU is out-of-stock at a top retailer

Flag OOSInvestigate root causeDispatch fixConfirm restock
Promo

Regional promotion is under-performing

DiagnoseCompare regionsAdjust termsMeasure
Launch

New item hitting shelves next month

Generate checklistAssign ownersAutomate briefsTrack go-live
Sales

Buyer meeting prep in 20 minutes

Pull POS + shareDraft talking points@Sales reviewsExport deck
Ecommerce

Content scores dropping on Amazon PDPs

Audit listingsGenerate fixesRoute for approvalPush updates

Your data stays yours. Every action has a trail.

Shopped is built for teams that need AI to be powerful and governed — where complete privacy isn't a feature, it's the foundation.

Zero data retention

Your data is never used to train models. LLM calls run on a private cluster with zero retention. Inputs and outputs are yours alone.

Complete audit trail

Every agent action, every human approval, every data query — logged, timestamped, and attributable. Role-based permissions and gated write-back to live systems.

Your infrastructure

VPC deployment, API-first architecture, and exportable formats. No lock-in, and nothing leaves your perimeter without your say-so.

Questions we get asked a lot.

Retail media platforms (Amazon, Walmart, Instacart, Criteo), POS and syndicated data feeds, inventory and supply chain feeds, trade promo systems, and flat files like spreadsheets and CSVs. If it has an API or an export, we can connect it.
Only if you let them. By default, every write-back action requires human approval. You control the gates: fully manual, semi-auto, or fully autonomous—per action type, per team, per system.
BI tools help you see what happened. Shopped helps you decide what to do and then do it—with your team, in real time, with audit trails. Think of it as the layer between insight and execution.
Yes. Shopped supports VPC deployment and row-level access controls. Your data is encrypted in transit and at rest, and we never train models on your proprietary data.
Most teams are live within two weeks. Core integrations take a few days. Custom data sources and approval workflows take a bit longer depending on complexity.
Shopped is designed for cross-functional commerce teams of 5–200 people. If your team spans sales, marketing, ecommerce, and ops—and you're tired of stitching together decisions across Slack, email, and spreadsheets—you're in the right place.

Ready to play as a team?

Get early access to Shopped and see how your commerce team can move faster—together.

Get startedSee the demo again ↑