Too much of a good thing?
Get control of all your enterprise and external data for more informed, accurate, and timely business decisions. aiMatch connects and reconciles data from disparate data sources, and fills in missing data, enabling more accurate forecasts and plans – even with limited historical data.
It’s time to reverse the 80-20
aiMatch for AI-powered
data reconciliation
200+ data integrations
Provides seamless access to over 200 enterprise and external data connectors for faster time to value. Don’t see what you need? Our customer success team has you covered.
Feature engineering with auto-correlation
Enhances model performance by selecting the most useful variables for the predictive model for both supervised and unsupervised learning.
Data stitching
Ingests datasets as inputs, learns the relationship between columns, and uses similarities between rows to stitch. Continuously improves model confidence for increased data quality.
Scalability and performance
Handles increasing data volumes and user loads with ease leveraging computationally-efficient LGMs and scalable architecture.
Data governance
Provides role-based access controls and permissions to ensure data is used properly. Works with enterprise data to eliminate data leakage and hallucinations.
We work in harmony
Testimonials
Frequently
asked questions
Ikigai offers over 200 pre-built connectors for all major data sources, such as AWS, Shopify, SAP, MongoDB, Google Drive, and much more, so that you can quickly connect to common enterprise data sources.
The eXpert-in-the-loop (Xitl) functionality integrates domain expertise into the reconciliation process, so that the model can improve its understanding of data relationships, improving data quality and speeding time to value.
There are over 200 built-in connectors provided by the Ikigai platform, providing fast access to the most commonly used enterprise data sources. New connectors can be added as needed by the Ikigai data team.
aiMatch does not require common columns to match data sets as it looks at the entire dataset to find matching entries. Using AI, it can overcome formatting inconsistencies, typos, and even missing data.