AI search engines recommend products based on structured catalog data. Your agentic copilot monitors every SKU, surfaces the gaps costing you visibility in both traditional and AI search, and delivers structured fixes your team approves and deploys, at any catalog scale.
Full visibility and complete control at every stage, from monitoring to deployment.
Always-on catalog intelligence for AI search
Continuous scans across every SKU evaluate completeness, structural integrity, and readiness for both marketplace compliance and AI search surfaces. No cron jobs, no manual audits.
Surface what makes products invisible to AI
Your agent evaluates product data against marketplace requirements and AI search patterns, surfacing the gaps that make products invisible to ChatGPT, Perplexity, Google AI Overviews, and traditional search. Prioritize compliance, AI readiness, or both.
Structured fixes, not guesswork
The agent generates field-level fixes with full reasoning: what's changing, why it matters, and which standard requires it. Surgical improvements, not bulk rewrites.
Your team controls every change
Nothing touches production without team approval. Review patches individually or in bulk. Approve, reject, or modify. The agent learns from your decisions over time.
Deploy approved changes instantly
Approved patches deploy directly through your existing connectors: Shopify, custom feeds, or any integrated platform. No export files, no dev tickets. Every deployment is versioned and reversible.
Every recommendation traces to a documented marketplace requirement or search-readiness standard. Focus on compliance, modern search trends, or both. The citation is always there.
A curated library of marketplace and platform standards, documented, versioned, and citable from day one.
Author internal naming conventions, category policies, and channel-specific rules that the agent enforces alongside marketplace requirements, with the same rigor and traceability.
Every patch includes the rule it's based on, the standard it comes from, and why it matters. No black box. Trace every recommendation to its source, whether that's a Google spec, a Schema.org requirement, or a custom standard you defined.
Teams are stuck in manual workflows that can't keep up with the speed, scale, and precision modern search surfaces demand.
A shared view of AI readiness and a shared workflow for improving it, across every team that touches product data.
Weeks spent manually auditing listings and updating spreadsheets across channels
Focus on strategy while the agent handles data hygiene. Approve changes in minutes, not months.
Products invisible to AI search engines. ChatGPT, Perplexity, and Google AI Overviews skip over poorly structured catalog data
See exactly which data gaps block AI search visibility, fix them systematically, and ensure every product is structured for both traditional and AI-powered discovery.
Manually normalizing and enriching catalog data across thousands of SKUs
Standardize your entire catalog against marketplace requirements at scale. The agent proposes fixes; your team validates.
No way to quantify the cost of bad product data or the ROI of fixing it
AI readiness scores, gap-to-revenue mapping, and measurable before-and-after metrics.
Every team gets the scope and permissions they need. Configurable across channels, categories, fields, and stakeholders.
Focus the agent on what matters: on-page optimization, structured data, specific categories, or individual launches. As broad or narrow as needed.
Merchandising reviews copy. Search teams focus on structured data. Leadership sees metrics. Same platform, permissions scoped to each role.
Choose which attributes the agent monitors: title structure, description length, image alt text, Schema.org properties. Your team decides.
Define and enforce rules per channel so every destination (Google Shopping, Amazon, Shopify, wholesale) gets the data it requires.
Configure standards and enrichment priorities by product category (apparel, electronics, food and beverage) for precision at scale.
Define who can approve what, require role-based sign-off, and set escalation paths for high-impact changes.
The agent adapts to your processes and priorities, not the other way around.
Every product is continuously evaluated against marketplace standards. When data drifts or standards change, your team knows first.
Ask your catalog questions like you'd ask an analyst. Surface insights dashboards can't show. Your agent answers with data, not opinions.
The agent validates incoming product data against every relevant standard before launch: titles, descriptions, structured data, and category mappings normalized automatically.
Inherited feeds, inconsistent formatting, and legacy data structures, cleaned up systematically. The agent identifies patterns and proposes standardized fixes deployable in bulk.
Each channel has unique data requirements. Your agent maps your catalog against each platform's rules and surfaces exactly what needs to change, per channel, per product.
ChatGPT, Perplexity, and Google AI Overviews are major product discovery channels. Your agentic copilot evaluates whether your catalog data is structured for AI comprehension and delivers the exact fixes needed to win AI search recommendations.
Same depth of analysis, same standards, same workflow, whether you manage 500 SKUs or millions across multiple storefronts.
Your agent is ready when your team is.