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Higher education data platform
Higher education AI platform

Higher education AI for your next report

Bring one enrollment, retention, or leadership report. See how Doowii connects the underlying systems, builds it around your definitions, and keeps it current. Our team manages the data platform and the work behind it.

See a reporting workflow

What we’ll cover in your demo

  • Your sources. How SIS, LMS, CRM, and local data come together.
  • Your report. The answer, definitions, and source context in one view.
  • The ongoing work. How Doowii maintains the connections and refreshes the reporting.

No data upload needed to start the conversation.

Read the WGU Labs pilotSOC 2 Type II report

Start with one report

See how your reporting could work

Tell us where you work. We’ll arrange a focused demo around your reporting priorities and follow up within one business day.

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Direct answer

What is a higher education data analytics and AI platform?

A higher education data analytics and AI platform brings campus data, shared definitions, permissions, analysis, reporting, and AI into one operating environment. Authorized teams can investigate new questions, run recurring reports, monitor defined indicators, and build predictive workflows without assembling a separate tool and pipeline for each use case.

Doowii manages the platform and performs the analytical work on top of it. Campus leaders retain ownership of meaning, access, validation, and decisions while Doowii handles the connections, models, maintenance, reports, monitoring, and AI workflows that keep the work moving.

Doowii gives higher education teams a managed data platform and an AI data team in one product.

Independent context

  • 2025 EDUCAUSE AI Landscape Study: Independent higher education context on AI strategy, leadership, policies, use cases, and workforce readiness.
  • When AI Meets Data: An EDUCAUSE Review account of the institutional definitions, governance, and security questions that emerge when AI reaches campus data systems.
  • NIST AI Risk Management Framework: A voluntary framework for considering governance, context, measurement, and management across the AI lifecycle.
The work behind the answer

Analytics should not add more work for your data team

Campus analytics stalls when every new question requires another extract, definition debate, dashboard, and maintenance cycle. Doowii takes on that work as part of the platform.

01

One definition across the work

Enrollment, persistence, census, program, cohort, and student success can each have several valid meanings. Doowii maps the definitions your institution uses and applies them consistently across questions, reports, and models.

02

Cross-system analysis by default

A useful question may require SIS, LMS, CRM, advising, financial, and local data. Doowii reconciles identities, timing, hierarchies, and data quality so the analysis starts with the full approved context.

03

Work that stays current

Doowii refreshes recurring reports, watches defined indicators, and maintains the data workflows behind them. Authorized teams can review the sources, calculations, assumptions, and changes without rebuilding the analysis each term.

Managed from end to end

Bring Doowii a priority, not a platform project

Doowii operates as your AI data team. We turn an institutional priority into a maintained data and analytics workflow while campus stakeholders set the purpose, meaning, access, review, and response.

Explore the managed platform
  1. 01

    Define the decision and owner

    Start with the question, who needs the answer, what decision it may inform, and who is accountable for definitions, validation, and follow-up.

  2. 02

    Connect the approved context

    Bring the required campus sources, identities, time periods, hierarchies, and institution-owned definitions into one governed model.

  3. 03

    Build the analytical workflow

    Configure the questions, recurring reports, monitored indicators, or predictive analysis the team needs. Apply access rules and preserve methodology and source context for review.

  4. 04

    Validate, use, and monitor

    Authorized stakeholders test the result against known cases, document its limits, decide how it enters the workflow, and revisit it as data, definitions, and conditions change.

Doowii connects, runs, and maintains the data workflow behind the answer.

See it on your campus
Concrete campus workflows

What your AI data team can deliver

Start with work already waiting on a data team. Doowii can turn it into a repeatable workflow on the same managed platform.

  • “A weekly admissions funnel report that shows where deposits or registration steps changed, then flags the segments behind the movement.”

  • “A retention model that refreshes on an approved schedule, surfaces contributing factors, and routes the result to the right team for review.”

  • “A program health view that combines enrollment, course progression, completion, and financial context using the same definitions as leadership reporting.”

  • “A cabinet report that rebuilds itself, explains what changed since the last refresh, and preserves the source and calculation behind each metric.”

  • “An IPEDS peer analysis that compares an institution-defined measure with selected peers and makes differences in definitions visible.”

One managed platform

Data analytics, predictive models, and AI on one foundation

Doowii connects the work required to make campus data usable with the analysis teams expect from it. The same governed foundation supports reporting, new questions, monitoring, forecasting, and AI.

Questions and recurring reports

Ask a new question, create a repeatable report, or trace a change back to its calculation and approved source context without opening another data ticket.

Predictive analytics

Build, validate, and refresh models on approved institutional data. Surface contributing factors and limitations so authorized teams can review the result before it informs action.

Monitoring and AI workflows

Watch defined metrics, explain meaningful changes, and support natural-language analysis using the same permissions, definitions, and governed data as institutional reporting.

AI outputs are analytical inputs, not institutional decisions. Institutions remain responsible for use-case approval, validation, access, fairness review, interpretation, intervention, and all consequential decisions.

Frequently asked questions

Questions about higher education ai platform

What is a higher education data analytics platform?

A higher education data analytics platform connects approved campus data, applies institutional definitions and permissions, and supports analysis across enrollment, retention, programs, finance, operations, and reporting. Doowii manages that foundation and the analytical work on top of it, including questions, recurring reports, monitoring, predictive analysis, and AI workflows.

How is Doowii different from a dashboard or general AI chatbot?

Dashboards usually present a fixed set of views, while a general chatbot generates language from the context it receives. Doowii operates the campus data foundation and carries it into new questions, recurring reports, monitored indicators, predictive analysis, and AI workflows. Each result can use approved institutional data, definitions, permissions, methodology, and source context.

Which campus data can support AI analytics?

Depending on the approved use case, sources can include SIS, LMS, CRM, ERP, advising, financial aid, assessment, warehouse, IPEDS, and institution-specific data. The exact scope depends on source access, licensing, permissions, history, quality, definitions, and the decision the institution wants to support.

How does predictive analytics work in higher education?

Predictive analytics uses historical and current institutional data to estimate a future measure or identify patterns that may warrant review. A useful workflow defines the population, outcome, time window, contributing data, validation method, refresh schedule, and people responsible for interpretation. Doowii can build and operate that workflow on the same managed platform as the institution's reporting and analysis.

Can one department or college begin before the whole institution?

Yes. A department, college, or team can begin with one approved priority and the systems required for that workflow. The governed connections, identities, definitions, and permissions can then support additional teams and workflows on the same managed platform as the institution is ready.

Does AI analytics replace institutional research or campus data teams?

No. AI analytics can expand governed access to questions, reports, and monitored indicators. Institutional research, data, security, privacy, and functional teams still define meaning, approve access and use cases, validate outputs, and retain responsibility for institutional decisions.

Does Doowii make decisions about students?

No. Doowii supports reviewable analysis on approved data. Indicators and predictions can highlight patterns that warrant closer review, but they do not determine a student's intent, diagnose a cause, prescribe an intervention, or replace institutional judgment.

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Meet Doowii at EDUCAUSE 2026

Bring one campus data or AI priority to a focused 20-minute conversation with the Doowii team in Denver.

Request an EDUCAUSE meeting
See it in your context

Give your campus an AI data team

Bring us one reporting, analytics, or predictive priority. We will show how Doowii can connect the required data, run the workflow, and keep it current on one managed higher education platform.

See a reporting workflowHigher education overview