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Showing 3 open source projects for "share"
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Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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MeridianLink One: A Unified Banking Software Solution for All SaaS Products and ServicesMeridianLink® Opening simplifies and accelerates digital account opening with a streamlined platform built for speed, security, and scalability. It supports a full suite of deposit products—checking, savings, CDs, and IRAs—while delivering a consistent, omnichannel experience across all channels. Through seamless integration with core and digital banking systems, as well as hundreds of trusted third-party providers, it automates data entry, ID verification, credit checks, and fraud protection. Flexible workflows and intelligent decisioning help institutions increase conversions, reduce abandonment, and cross-sell more effectively—all while supporting compliance and a frictionless consumer experience.
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
Unlock unlimited possibilities with synthetic data. Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. -
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Feathr
A scalable, unified data and AI engineering platform for enterprise
...Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features) across team and company. Feathr is particularly useful in AI modeling where it automatically computes your feature transformations and joins them to your training data, using point-in-time-correct semantics to avoid data leakage, and supports materializing and deploying your features for use online in production. -
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WhyLogs Java Library
Profile and monitor your ML data pipeline end-to-end
This is a Java implementation of WhyLogs, with support for Apache Spark integration for large scale datasets. Understanding the properties of data as it moves through applications is essential to keeping your ML/AI pipeline stable and improving your user experience, whether your pipeline is built for production or experimentation. WhyLogs is an open source statistical logging library that allows data science and ML teams to effortlessly profile ML/AI pipelines and applications, producing log...
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