Machine learning (ML) models can clean and enrich data far better and faster than manual approaches. That's how Amazon and other industry leaders scale their digital operations. Learn more, because this approach can transform your business too!
This is for you if:
Your team spends hours each week cleaning spreadsheet data
Tender response requires laborious material matching
Supplier file updates take too long, squeezing margins and marketing
Data-driven goals like growing your online catalog never get done
Distributor Data Solutions
Continuous Improvement Director
WrangleWorks thoroughly cleaned and enriched a million material records in a very efficient manner. The resulting reference data and associated ‘matching ’ has accelerated our new customer onboarding process, reducing the cycle time by more than 30%.
Automating Data Work
APIs & Orchestration
Wrangling data is easy with APIs. They can retrieve dirty and inject cleaned data into any process or system, including a spreadsheet.
Data work often requires blending multiple data sets. Smart APIs can match and integrate data automagically.
Orchestration of data flows is well suited to the cloud. Well designed pipelines run reliably and "lights out."
APIs and cloud automation can be deployed and operated with minimal IT investment.
Here's a simple example of using Natural Language Processing to extract product attributes from a description.
We have decades of experience deploying advanced analytics into industrial distributors & manufacturers.
For 20-plus years, I've helped industrial companies adopt tech. WrangleWorks solves distributor data problems, making digital dreams come true.
My career has been rolling out applications for a channel-centric, global manufacturer. I love helping distributors make the most of their supplier data.
Been there, done that (data) for an MRO distributor. We're using the latest cloud tools and ML techniques; doing data 100x faster than typical manual approaches.