entrosift
Aerial view of a working cargo port and global commerce infrastructure
THE DATA LAYER FOR AI COMMERCE

Commerce moves fast.
Give AI the full picture.

From fragmented product data to AI-ready intelligence.
One data foundation for models and shopping agents.

Explore the platform ↓
REAL-WORLD COMMERCE. MACHINE-READY CONTEXT.Scroll to explore ↓
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BUILT FOR THE NEXT ERA OF COMMERCE

Better commerce AI
starts with better data.

Product catalogs live in silos. Attributes don’t match. Prices change. AI needs a coherent view of it all.

Entrosift connects, structures, and delivers commerce data—so your team can build models that understand products and agents that help people shop.

THE ENTROSIFT PLATFORM

From source to intelligence.
Connected at every layer.

One foundation.
Every AI experience.

See how it connects ↘
COMMERCE DATA INTEGRATION

Many sources.
One coherent catalog.

Bring product feeds, marketplace data, and merchant catalogs into a shared foundation. Resolve inconsistent formats before they reach your models.

  • Catalog and feed integration
  • Cross-source product mapping
  • Price and availability context
Explore the data flow ↗
ENTROSIFT / DATA ENGINEILLUSTRATIVE FLOW
Merchant catalogs ↘Product feeds →Marketplace data ↗
UNIFY & NORMALIZE
Unified product recordJSON
{
  "product_id": "prd_042",
  "title": "Everyday Headphones",
  "category": "Audio",
  "offers": [ … ],
  "source": "merchant_feed"
}
FRAGMENTED INPUTS → STRUCTURED CONTEXT
COMMERCE CONTEXT, END TO END

A direct line from your data
to what AI can do with it.

01 / INGEST

Connect the sources.

Bring together the product data your business already has.

02 / PROCESS

Make it meaningful.

Normalize taxonomies, reconcile entities, and structure attributes.

03 / ACTIVATE

Put context to work.

Deliver model-ready datasets and agent-accessible tools.

BUILT FOR SHOPPING AGENTS

Give your agent
a better way
to shop.

A model can understand a request. It needs commerce context to answer it well.

Expose structured product discovery through the Model Context Protocol. Help agents find relevant products, compare attributes, and ground recommendations in source data.

Explore an MCP interaction ↘
YOUR COMMERCE DATA. AN AGENT-ACCESSIBLE INTERFACE.
entrosift / mcp playground↗
TRY AN ILLUSTRATIVE REQUEST
↳

Find wireless headphones under $150 for everyday commuting.

MCP TOOL CALL EXAMPLE
products.search({
  "query": "wireless headphones",
  "max_price": 150,
  "currency": "USD"
})
STRUCTURED RESPONSE
Everyday Wireless Headphones$129.00

Over-ear · Noise cancellation · 30h battery

↗ Source-linked product context
Example data and tool schema. No live product search.
BUILT AROUND YOUR USE CASE
DATA THAT GOES FURTHER

One data layer.
A world of possibilities.

Rows of shipping containers at a busy commercial port
01 / AI TEAMS

Teach models
real-world commerce.

Structured product datasets for training, retrieval, and evaluation.

02 / AGENT BUILDERS

Build shopping agents
with useful context.

Connect discovery and comparison experiences to commerce data through MCP.

03 / COMMERCE BUSINESSES

Make your catalog
ready for AI discovery.

Turn fragmented merchant data into consistent, machine-readable product context.

OUR APPROACH

The details
make the data.

Useful AI starts with the fundamentals: consistent structure, clear sources, and context that fits the task.

01

Commerce is the context.

Products, variants, attributes, and offers belong together. Shape the data around how commerce actually works.

02

Quality before quantity.

Align schemas and taxonomies, identify duplicates, and surface missing fields before downstream use.

03

Build for both models and agents.

Serve datasets for model workflows and structured interfaces for agent experiences from a common foundation.

LET’S BUILD WHAT COMES NEXT

Your commerce data.
Ready for the AI era.