JAI empowers you to classify, complete, enrich, and validate your data in a scalable and cost-efficient way. We are fast because we know you must meet critical service level agreements!
We are agnostic of your current data stack bridging IT with business again. Contact us to know how JAI can help you today!
Inconsistent data entry companies with increasing velocity, greater variability, and volume.
Sub-optimal decisions are made based on incomplete or inaccurate reporting and analytics.
Sub-optimal decisions reduce margins, delay time-to-market, and undermine customers’ trust.
A shortage of data professionals is predicted in the coming years, making it impossible to hire professionals with the necessary skills to clean, filter, and integrate your data.
of CEOs are concerned about the quality of the data they are basing their decisions on
of data scientists say they spend their time finding, organizing, and cleaning data instead of analyzing it
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Investments in AI-based tools to assist in data sanitization and consolidation returns an average of 200% increase in productivity!
The manual process is slower, more expensive, and often requires specific knowledge of the business area.
JAI uses AI to identify irregular patterns in data - and store their machine representations (vector embeddings)
Changes are automatically staged into a checkup table for human inspection
Imagine spending time only validating your product classification instead of manually cleaning it. Imagine autocompleting a column in your data warehouse - or spreadsheet if you prefer -with more than 80% accuracy.
No more garbage in, garbage out. Watch our demo and see how JAI can make it all possible.
Legacy ERP systems and inconsistencies in manual input data - in multiple languages - have forced this multinational packaging supplier with 200 locations in over 40 countries to think outside the box! Their procurement team has around 20.000 unmapped values monthly to classify (e g., category/subcategory) to present a spend analysis to the business leaders by the end of the month. These are their main gains using JAI:
increase in productivity (around 2h weekly verifying results vs. 10h weekly of manually cleaning data)
increase in productivity (around 2h weekly verifying results vs. 10h weekly of manually cleaning data)
increase in productivity (around 2h weekly verifying results vs. 10h weekly of manually cleaning data)
Long (6+ months) - hire and train resources, establish best practices and build your own solution
High - need to hire more people and resources as the volume of data increases
One-time - the data is cleaned, accuracy is measured, and the project ends
Difficult - dependency on IT teams to maintain the system on top of their other usual responsibilities
Medium - focus on only data validation, accuracy and, uniqueness
Short (2-3 weeks) - engage directly with our experts, sign and configure using JAI
Low - add more data for JAI to manage without needing to add more people or resources
Continuous - data is constantly cleaned and enriched, the more you use JAI, the better the quality
Simple - outsource maintenance to JAI and give data observability to all teams (not just IT)
High - focus on data validation, accuracy, uniqueness, completeness, consistency and speed
