Amway Nutrilite adopted MatrixOne Intelligence to build a unified AI data engineering platform, cutting average data preparation time for new AI applications by 80%.
Amway is one of the world's largest direct-selling companies, with its Nutrilite brand among the best-known nutrition and wellness names globally, operating across manufacturing, distribution and a large network of independent business owners.
The customer is a world-renowned health supplement retail brand. To accelerate intelligent transformation, they launched an AI Factory initiative to build AI assistant applications across marketing, customer service, and finance.
Critical knowledge assets were scattered across CMS, S3, and databases in multiple formats (PDF, HTML, structured data). Independent data integration per application would create a complex many-to-many architecture with duplicated effort and inconsistent data quality.
The customer adopted MatrixOne Intelligence to build a centralized AI data engineering platform with the principle of 'process once, share everywhere.'
The platform auto-ingests data from S3, CMS, and Dataphin via built-in connectors; processes it through MatrixPipeline's visual workflows with intelligent parsing, chunking, and vectorization; and stores AI-Ready data in a unified MatrixOne vector knowledge base.
The platform successfully decoupled data engineering from AI application development, reducing average data preparation time for new applications by 80%.
Standardized central data processing ensured consistent data quality across all AI applications, significantly improving RAG application accuracy and trustworthiness.
The platform now powers multiple core applications including AI Contract Review, Sales Copilot, and AI Health Assistant — with contract review time reduced from 16 days to 1 minute.
Amway's legal team reviews a high volume of commercial contracts — supplier agreements, distributor terms — and comparing each against standard clauses by hand is slow and easy to skip.
A contract review assistant on the same AI foundation compares incoming contracts against the standard clause library, company policies and compliance rules, flagging deviations and risks so legal reviews rather than reads.
Business users previously queued behind the data team for figures that were simple to ask for but slow to obtain.
NL2SQL lets them ask in everyday language and get results directly, freeing the data team from repetitive extraction work.
Nutrilite product development depends on continuously tracking nutrition science literature, where manual search and synthesis is slow and never exhaustive.
A deep research assistant on the same foundation retrieves and synthesises the evidence base, supporting formulation research and efficacy validation with cited material.