42technologies
42technologies provides a retail data and AI platform that consolidates sales, inventory, and financial metrics from systems like Shopify and NetSuite into a single validated source of truth. The platform delivers AI-ready datasets, analytics dashboards, and an MCP server that enables AI assistants to answer operational questions such as predicting stock-outs.
- Retail Technology
- Data & Analytics
- Artificial Intelligence
- Enterprise Software
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Retailers struggle with fragmented data across operational systems like Shopify, NetSuite, and finance platforms, leading to mismatched net sales figures, inventory discrepancies, and unreliable metrics. This data inconsistency prevents teams from trusting their analytics and limits their ability to deploy AI effectively for operational decisions.
Solution
42technologies provides a retail-focused data and AI platform that consolidates sales, inventory, and financial metrics into a single, validated source of truth. The platform automatically reconciles discrepancies between systems—for example, matching Shopify net sales of $51.6M with NetSuite's $48.2M—so teams can trust the numbers they work with. It delivers AI-ready datasets and analytics dashboards that track key performance indicators such as units per transaction, conversion rates, and average order value. The platform also includes an MCP server that lets AI assistants query retail data directly, enabling use cases like predicting which products will stock out in a given week.
Target Audience
Primary customers are retail operations teams, finance leaders, and data/AI practitioners at omnichannel retailers who need consistent, trustworthy data across e-commerce platforms and ERP systems.
Features
- Automated reconciliation of net sales, margin, and inventory data across Shopify, NetSuite, and finance systems into one validated dataset
- AI-ready data foundation designed for direct consumption by machine learning models and AI tools
- Analytics dashboards tracking KPIs including net sales, units per transaction, conversion rate, average order value, and inventory on hand
- MCP (Model Context Protocol) server that enables AI assistants to answer operational questions like "What products will stock out this week?"
- Filterable views by store and item with weekly performance comparisons against goals