AI Operations for Marketing and Merchandising

Automate your marketing and merchandising operations with AI

StyleBoard turns messy vendor files, product data, and customer data into clean, automated operations. We go deepest in furniture and home decor, where a raw vendor file becomes import ready catalog data in a fraction of the usual time. Marketing teams run the same engine to sharpen lifecycle and email.

Currently in the ATDC accelerator at Georgia Tech.

How it works

This is not a set of tools. It is a reasoning engine for product information.

One messy input from a vendor. One engine that understands products, images, taxonomy, and your business rules. The outcomes you actually need, ready for any system you run.

Messy product information in
Raw vendor files
Spreadsheets · PDFs · images · spec sheets · catalogs
The intellectual property
StyleBoard Engine
Understands products, images, taxonomy, and business rules
Not another PIM. Works alongside your existing ERP, PIM, DAM, and ecommerce platform, producing the clean records they depend on.
01
Import ready data
Clean, mapped, structured
02
Vision classification
Into your own hierarchy
03
Image standardization
Cleaned, cropped, to spec
Quality validation Runs across every outcome, not as a final step
Clean, structured output out
ERP
NetSuite, Dynamics
PIM
Salsify, Akeneo
Ecommerce
Shopify, or any
DAM
Bynder, Cloudinary
Marketplace
Amazon, Wayfair
Your own system
Proprietary feeds
Proof

A vendor file of more than a thousand products, import ready in a fraction of the time.

For a premium home furnishings retailer running a catalog of more than 5000 SKUs, StyleBoard took a raw vendor assortment file and produced a clean NetSuite import in a single pass. Work that normally consumes days of manual entry compressed into a run you can watch happen.

1000+
Products in one file
5000+
SKU catalog
1 pass
File to import

The quality checks came along for free. Duplicate SKUs, a physically impossible dimension, and a missing spec, each surfaced and ranked by what it would actually cost the business. Catching errors is the byproduct. Compressing the time to a finished, sellable catalog is the point.

Read the full breakdown →
Merchandising Operations

The furniture and home decor catalog, automated end to end.

Everything between a vendor sending you a file and a customer seeing a finished product page.

Data

Product Data Transformation

Any vendor format in. Clean, mapped, import ready data out. This is the work already proven on a live NetSuite catalog.

Taxonomy

Product Classification

Products categorized to your own taxonomy using vision and text models, not manual tagging.

Content

AI Product Content

Titles, descriptions, and SEO copy generated in your brand voice, ready for review rather than written from scratch.

Media

Image Processing

Resizing, cropping, and background work at catalog scale, held to a single consistent spec.

Systems

ERP and Shopify Automation

NetSuite imports and Shopify syncs produced without manual data entry.

Quality

Catalog and Website QA

Errors caught before they reach a customer, ranked by business impact rather than by ease of detection.

Marketing Operations

The same intelligence, pointed at your customer data.

For ecommerce brands running lifecycle and email programs, StyleBoard reads every send against your own performance data and tells you what to change.

Lifecycle

Welcome and Lifecycle Intelligence

Where a welcome flow wins and loses, and the offer architecture that actually moves conversion in the first weeks after opt in.

Quality

Email and SMS QA

Prices, links, availability, and collections verified against your live site before a send goes out.

Analysis

Performance Analysis

Which sends build multi category buyers, and when send frequency starts costing more than it earns.

check@styleboard.ai
Add it to your next test send. Get a QC report back in minutes. No signup.
Who builds this

Built by an operator, not a guess about how operations work.

Former VP of Marketing and eCommerce helping manufacturers and retailers automate marketing and merchandising operations with AI.

StyleBoard is built and led by Vivek Singhania, Founder and CEO. He spent five years running merchandising and marketing operations inside a premium home furnishings retailer with a catalog of more than 5000 SKUs, and led marketing at large consumer brands before that. He is a Lean Six Sigma Black Belt with an MBA from the University of Chicago Booth School of Business. StyleBoard pairs that operating knowledge with modern AI to automate the work that traditional software still leaves manual.

Send us a messy vendor file.

We will send back clean, import ready data and a QC report. No signup. Just the file.

Book a Demo →

or email a file to vivek@styleboard.ai

© 2026 StyleBoard AI · vivek@styleboard.ai · AI Operations for Marketing and Merchandising