Nuro Retention Platform

How do you become the best in student success and retention?

We believe it starts with developing the most thoughtful and advanced software for higher education.

We’ve believed in the potential of data from our inception, so we developed a powerful middleware tool set that identifies trends and patterns in consumed data which is then normalized and tagged in time to create traceable checkpoints of behavioral data. Using neural algorithms, augmented with graph database technologies, Nuro Retention is able to consume, combine and normalize multiple, disparate data sets.

The data is then consumed by the Nuro Retention platform and made available to other school credentialed users and applications via  APIs, to inform the personalized case management of each and every student. Wanna really geek out? Download our Middleware FAQ sheet and impress your IT department. And yes, privacy is a big deal to us.

icon-insightInsight

Proprietary middleware consumes all school data sources, analyzes and scrubs the data and makes it available to both the Nuro Retention platform as well as other school software applications.

We call this our ‘neural network’, which allows us to analyze all data points (nodes) and raise alerts based upon granular risk assessments – without over alerting – nobody likes a chicken little.

Constant monitoring with risk assessment, automated flags, actions and cohort creation for all students. 

Use survey tools to create, deliver, and deploying automated actions based on response.

Resolution

Complete case management, period. Engage all stakeholders with centralized, shared documents and notes, milestones, student timelines, video chat, text messaging and voting.

A student portal – Self-serve salvation, even on mobile.

Faculty progress reports for cohorts or classes with unreported LMS data

Empower all campus success stakeholders to raise a flag for all issues affecting students including academic, mental health, financial insecurity and housing.

Analysis

Custom Reporting with selected data points for cohort monitoring and super granular views of  student status in each enrolled class. Reports for individuals, departments, and institutions. 

Predictive, proactive analytics that actively search for similar cognitive and non-cognitive data between present and prior year students to predict weekly progress for all students.

Integrate data from additional sources to provide further insight into individual cases, cohorts, departments, or schools.