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Cernel uses a few core concepts that work together: your products are organized into a taxonomy of categories, attributes define what data each product needs, and AI agents generate that data. Understanding how these pieces connect will help you get the most from the platform.

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The big picture

Here’s how product data flows through Cernel:
  1. Products come in from your connected integration (Shopify, CSV, Feed, or API)
  2. Cernel automatically classifies each product into the right category in the Cernel Taxonomy
  3. Attributes are configured on categories to define what data products need
  4. AI agents generate attribute values, using your prompts, your brand context from Data Sources, and, where you’ve set it up, the output of upstream agents
  5. You review and approve the generated content, or let it push automatically if you’ve turned approval off
  6. Enriched data syncs back to your store or export channel
Each step builds on the previous one. The taxonomy drives what attributes exist, attributes drive what agents produce, and agents drive what content your customers see.

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Key concepts

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Cernel Taxonomy

The Cernel Taxonomy is a hierarchical category structure maintained by Cernel, like Apparel & Accessories > Shoes > Running Shoes. When you import products, Cernel automatically classifies each one into the right category, so you don’t build or manage the taxonomy yourself. Every product ends up in a category. Categories are the organizing principle for everything else in Cernel. When you add an attribute to a category, it automatically applies to all subcategories beneath it. This means you configure once at the right level and it flows down the tree.
The Cernel Products page showing the taxonomy sidebar with Apparel & Accessories expanded into Clothing, Clothing Accessories, and Shoes subcategories, each with product counts

Learn more

Full guide to setting up and managing your Cernel Taxonomy.

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Attributes

Attributes are the data fields that AI fills in for your products: descriptions, meta titles, materials, colors, sizing, and more. You configure attributes on categories in your taxonomy, and they automatically apply to all subcategories. Cernel supports six attribute types:
TypeWhat it producesExample
TextPlain text contentProduct descriptions, meta titles
HTMLRich formatted contentLong descriptions with headings and lists
Single SelectOne value from a listGender: Male / Female / Unisex
Multi SelectMultiple values from a listMaterials: Cotton, Polyester, Elastane
External DataData from an external sourceGTIN matching
MediaImage contentAI-generated product images

Learn more

Deep dive into attribute types, configuration, and how they work across categories.

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AI Agents

An AI agent is a configured AI with a specific job: write a product description, extract materials, classify by gender, source product imagery, or anything else your catalog needs. You define what it should generate, the tone and style, any constraints, and the brand context it should draw on from your Data Sources. You can describe your intent in plain language and let Cernel write the prompt for you, or write it yourself. Before an agent goes live, you test it in a sandbox on real products with an agent chat that rewrites the prompt based on your feedback, plus version history so you can roll back. Agents can also depend on each other, letting one agent’s output feed into the next so you can chain work (for example, a meta description agent that reads the product description agent’s output). Cernel resolves dependencies and runs agents in the right order when you enrich. Agents are independent from categories. Create one “Product Description” agent and link it to the description attribute across your entire taxonomy. Update the agent’s prompt and every category picks up the change.
The Cernel agent editor showing a prompt configuration with synthesis instructions and Data Source references for product title and images

Learn more

Create agents, configure prompts, and run your first enrichment.

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Data Sources

Data Sources are your organization’s context library. Store brand guidelines, product specifications, target audience descriptions, and other reference material that you want AI agents to use when generating content. You create entries in Settings > Data Sources and reference them in agent prompts by typing /. The reference appears as a labeled pill in the prompt editor, making it easy to see which context is included. Update a Data Source once and every agent using it picks up the change.
The Cernel Data Sources settings page showing a folder explorer on the left and entry management on the right with options to create new folders and entries

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Enrichment and jobs

Enrichment is the process of running AI agents on your products to generate attribute values. You select products (individually or by category), choose which attributes to generate, and start a job. Cernel processes everything in the background and tracks progress on your Dashboard. After a job completes, you review the results. Each generated value can be approved, edited, or rejected before it syncs to your connected integrations. Review is optional. If you’d rather have enriched content push straight to your store without a manual approval step, turn off Approve Before Push in Settings > Global > Platform. Leave it on when you want a human check before anything goes live.

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Automations

Automations let you automatically enrich new products when they’re created. Set up a rule by selecting a category, defining optional product filters, and choosing which attributes to generate. When a new product matches the rule, enrichment runs automatically.
Automations only apply to newly created products. Existing products are not affected. Use manual enrichment for those.

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What’s next

Connect Shopify

Import your product catalog so you have products to work with.

Enriching products

Walk through generating AI content for your first products.