Shyna
Kovil AI Assistant
AI assistant. Verify important details with the Kovil AI team.
Ingest raw supplier spec sheet files autonomously. Convert unstructured tables and technical documents into SEO-optimized product titles, descriptions, and tag structures — ready for one-click review.
The Enrichment Pipeline
Ingest messy files, optimize for search engines, and draft catalog items automatically.
Agents monitor supplier emails or shared directories, parsing raw PDF or Excel specification files as soon as they arrive.
Models rewrite dry specifications into engaging, SEO-optimized product titles, descriptions, and feature lists in your brand's tone of voice.
Extracted attributes — weight, price, color, dimensions — are validated into strict, consistent variant schemas before anything is written.
Completed records post to Shopify GraphQL endpoints as draft products, ready for a merchandiser's one-click review and publish.
In Practice
A real deployment, walked step by step — from format-agnostic parsing to a multi-agent copywriting handoff to the draft-only publish gate that protects the storefront.
Kovil AI built an enrichment pipeline that parses a supplier's raw spec sheet, drafts SEO-optimized copy, and creates the product as a Shopify draft — turning a day of data entry into minutes of review.
Instead of a rigid template importer, the parsing agent handles wildly inconsistent supplier formats, normalizing dimensions, materials, and pricing into one strict schema before anything is written.
The Parser extracts raw fields, the Copywriter drafts brand-voice-aligned titles and descriptions, and the Schema Validator checks everything before the Draft Publisher creates the Shopify listing.
Every enriched product is created as a Shopify draft, never published automatically, and copy is checked against the brand's style guide before it ever reaches a reviewer's queue.
New supplier catalogs onboard in a single sitting instead of a week of data entry, with consistent SEO copy and zero schema errors reaching the live storefront.
Technical Features
Processes up to 5,000 unique supplier sheets per hour, converting messy structures into consistent variant schemas at scale.
Store your style guides inside the model context, ensuring description outputs match your brand aesthetic perfectly, every time.
Ensures attributes like weight, price, and color tags are formatted into strict schemas before committing, catching malformed data early.
Reads PDF layouts, Excel tables, and even scanned image-based spec sheets, normalizing wildly different supplier formats into one schema.
Walkthrough
A supplier emails a PDF spec sheet covering 40 new SKUs with inconsistent formatting across sections.
The parsing agent extracts each item's dimensions, materials, price, and available variants into a normalized table.
A copywriting model drafts SEO-optimized titles and descriptions for each item, matching your brand's established tone of voice.
All 40 products are created as Shopify drafts, flagged for merchandiser review rather than published live automatically.
The merchandising team reviews the batch in one sitting and publishes with a single bulk action, rather than 40 individual manual entries.
Compatibility
Manual Entry vs. Enrichment Agent
| Capability | Manual Data Entry | Kovil AI Enricher |
|---|---|---|
| Time per new product line | Often a full day of manual data entry | Minutes per batch, review-and-publish |
| Format handling | Breaks on inconsistent supplier layouts | Reads PDF, Excel, and scanned formats |
| SEO copywriting | Copy-pasted spec text, rarely optimized | Brand-voice-aligned SEO description generation |
| Data validation | Manual spot-checking, error-prone | Strict schema validation before commit |
| Publishing safety | N/A — manual process | Draft-only by default, human review required |
FAQ
Answers regarding description rules and draft approvals.
Partner with Kovil AI to map supplier files and deploy automatic description generators under a 2-week risk-free trial.