Meet the agent that
understands your catalog.
Talk to your product data in natural language. Surface gaps, generate fixes, and measure results. Connected to your performance tools so every insight is grounded in real data. Catalog activation at scale.
It watches. It fixes. It ships.
You stay in control.
Three things, done continuously, at a depth and speed no team can match manually.
Watches everything
Your agent evaluates every SKU against 40+ marketplace and platform standards. It knows what changed, what drifted, and what needs attention. Critical gaps always surface first.
- Google, Amazon, Shopify, Schema.org, and more
- Prioritized by revenue impact
- Runs 24/7, not when someone remembers
Generates real fixes
Not flags. Not suggestions. Structured, field-level patches with full reasoning: what's changing, why it matters, and which standard requires it. Diff previews before anything happens.
- Every fix cites a specific rule or standard
- Risk-scored with confidence levels
- Surgical changes, not bulk rewrites
Ships when you approve
Your team reviews and approves every change before it goes live. Approve one at a time or in bulk. Deploy through your existing connectors. Every deployment is versioned and reversible.
- Human-in-the-loop or auto-publish modes
- One-click deploy to your connected store
- Full audit trail of every change
CATALOG DASHBOARDCatalog Health
78/100
+4 this week
Products Monitored
12,847
All active
Issues Detected
234
31 critical
Fixes Ready
189
Awaiting review
Summer Collection: 47 products scanned. 12 missing structured alt text. Fixes generated.
ReviewGoogle Shopping feed: 3 products flagged for missing GTIN. Corrections drafted.
ReviewCategory mapping updated for 89 products. Schema.org compliance improved to 94%.
DoneReal patches. Real reasoning.
Review before anything changes.
Every fix shows you exactly what changed, the before and after, and the rule that triggered it. Nothing is a black box.
FIX QUEUEIMG_2847.jpg
Sage green linen midi dress, relaxed fit, front view on model
Rule: Google Shopping Image Alt Text Standard
Black crewneck tee. Organic cotton.
Organic cotton crewneck t-shirt in black. Relaxed fit, ribbed collar, pre-shrunk fabric. GOTS certified organic cotton.
Rule: Schema.org Product Description
Accessories
Accessories > Belts > Woven Belts
Rule: Google Product Category Taxonomy
Talk to your catalog
like you'd talk to your best analyst.
EKOM isn't just a surface-and-patch tool. It's a conversational layer across your entire product catalog. Ask questions in natural language, explore data relationships, flush out insights no dashboard can surface, and move from understanding to action in the same session.
Natural language, structured answers
Ask 'Which products in outdoor furniture are missing alt text?' or 'Show me the worst-performing category by data completeness.' Your agent answers with data, not opinions.
Explore, then act
Go from curiosity to action in one flow. Surface a gap, understand the reasoning, generate the fix, and queue it for approval. No context switching between tools.
Deeper understanding over time
Your agent learns your catalog's structure, attribute patterns, and category relationships. The more you use it, the sharper the insights and the better the fixes.
Your performance data
feeds the agent. Your team reads the results.
EKOM connects to GA4, Google Search Console, and other performance tools your team already uses. That context flows into the agent so every recommendation is grounded in real performance data, not assumptions.
Connect your performance stack
Bring in data from the tools your team already relies on. The agent uses this context to prioritize fixes by actual business impact.
- Google Analytics 4 for conversion and engagement data
- Google Search Console for search visibility and click-through
- Any analytics or BI tool via API integration
Your team measures the impact
Before-and-after metrics tied to every batch of changes your team approves. The brand drives the gains. EKOM makes it measurable.
- Catalog health scores tied to conversion and visibility data
- Before-and-after metrics on every approved batch
- Gap-to-revenue mapping so your team prioritizes what matters
Every recommendation traces
to a documented standard.
No opinions. No black boxes. Every patch cites the rule it's based on, the standard it comes from, and why it matters to your product's performance.
40+ pre-built standards
Google Merchant Center, Amazon, Shopify, Schema.org, and more. Documented, versioned, and ready from day one.
- Marketplace feed requirements across major platforms
- Schema.org structured data for product markup
- Discovery readiness for AI platforms and social commerce
Your own rules, same rigor
Author internal naming conventions, category policies, and channel-specific rules. The agent enforces them alongside marketplace standards with the same traceability.
- Brand-specific rules for titles, descriptions, and attributes
- Policies per category, channel, or region
- Versioned and updated as your standards evolve
One platform. Every team that
touches product data.
Same agent, same source of truth. Each team sees the view that matters to them.
Merchandising
Focus on strategy while the agent handles data quality. Approve changes in minutes, not months.
Search & SEO
See exactly which data gaps block visibility and fix them systematically across every discovery channel.
Product Data
Standardize your entire catalog against marketplace requirements at scale. The agent proposes; your team validates.
Leadership
Catalog health scores, gap-to-revenue mapping, and measurable before-and-after improvement metrics.
500 SKUs or 5 million.
Same depth. Same speed.
The same analysis, the same standards, and the same workflow whether you're a boutique brand or an enterprise with millions of products.
We connected on a Monday morning and by Tuesday our team was already reviewing fixes across 2,200 products. Honestly didn't expect it to move that fast.
Head of Product Data, Consumer ElectronicsConnect your catalog.
See what your agent finds.
One API. Under 24 hours. Your team reviews the first fixes.