Reason over your catalog — not just store it.
CataZenta is Agentic PIM — ten specialist agents propose catalog improvements; humans approve every write in the Agent Control Center. Zen AI, MCP, and REST APIs operate on the same governed catalog.
Traditional PIMs store attributes. CataZenta reasons over them: agent findings, enrichment, syndication readiness, and compliance — with humans in the loop before anything goes live.
Start with the Agentic PIM overview — propose → approve → publish — before diving into individual capabilities below.
The intelligence loop
Agent findings, enrichment, and conversational AI all feed the same path: propose → review → apply → syndicate.
| Stage | What happens | Where |
|---|---|---|
| Detect | Gaps, SEO weakness, taxonomy conflicts, compliance issues | Specialist agents · completeness · enrichment queues |
| Propose | Attribute updates, content drafts, classification fixes | ACC approvals · Content Studio · Zen AI suggestions |
| Review | Approve, reject, refine — individually or in bulk | Approvals · PIM workflows |
| Publish | Channel-ready export after gates pass | Syndication · quick_publish via MCP |
Catalog Quality measures open agent insights — not attribute fill rate alone. Completeness scores remain useful as publish gates; they answer a different question.
AI capabilities
Eight documented capability areas — each grounded in your families, attributes, channel rules, and audit trails.
Agent Control Center
Enable specialist agents, triage insights, review approval proposals, monitor catalog quality from findings.
AI enrichment
Fill gaps across thousands of SKUs — titles, bullets, specs — with Content Studio and completeness gates.
AI product content
On-brand copy per channel and locale — Amazon bullets, Shopify titles, SEO meta, B2B summaries.
Attribute extraction
Normalize supplier feeds, ERP text, and semi-structured input into your attribute model.
AI workflows
AI-assisted steps inside approval chains — enrichment, legal, brand, channel gates.
Conversational ops
Ask Zen AI in PIM or orchestrate tool chains in Claude, ChatGPT, and Cursor via MCP.
AI agents (MCP)
External clients automate search, enrich, publish, and audit with 90+ structured tools.
Product intelligence
Agent insights, completeness gates, channel readiness — decisions from one source of truth.
Five surfaces, one catalog
Every AI path reads and writes the same structured catalog — not a shadow database or CSV export.
| Surface | Who uses it | Typical work |
|---|---|---|
| Agent Control Center | Catalog ops, AI admins | Scheduled agent runs, approvals, Catalog Quality |
| Zen AI | Editors and managers | Ad-hoc questions, inline suggestions on product pages |
| Content Studio | Merchandising leads | Bulk enrichment jobs across families or imports |
| MCP | Developers, power users | Claude, ChatGPT, Cursor — tool-driven automation |
| REST APIs | Integrations, ERP, headless | Custom pipelines, batch jobs, syndication workers |
| Zen AI | Specialist agents (ACC) | MCP | |
|---|---|---|---|
| Interaction | Chat in PIM | Autonomous runs, missions | Tool calls in external clients |
| Persistence | Session chat | Insights + approval queue | Session-driven chains |
| Writes | Manual apply or workflow gates | Approval queue → apply | Named API tool calls |
| Best for | One product, one question | Continuous catalog intelligence | Developer automation |
Example outcomes
Real catalog operations teams run with Agentic PIM — not generic chat prompts.
| Outcome | How CataZenta delivers it |
|---|---|
| SEO descriptions from specs | Enrichment agent + brand voice rules → approval queue |
| Normalized product specs | Attribute extraction + enrichment across families |
| Automatic classification | Taxonomy agent → category assignments for review |
| Marketplace titles | Product content + channel length rules per Amazon, Shopify, B2B |
| Syndication readiness | Syndication agent insights before quick_publish |
| Compliance gaps | Compliance agent findings → workflow tasks for legal |
Step-by-step business flows → AI workflow examples
Intelligence in action
From ingest to channel — agent findings and completeness gates work together.
Deep dive on signals and APIs → Product intelligence
Start by role
Catalog / merchandising
Evaluating vs legacy PIM
Get started
- Read Agentic PIM overview — the propose → approve → publish loop.
- Open Agent Control Center — enable agents and review the approval queue.
- Pick a capability above matching your role (enrichment, MCP, product intelligence, …).
- Wire MCP or REST APIs when you need automation outside the UI.
- Monitor Catalog quality weekly — findings, not fill rates alone.
GO DEEPER