Education Intelligence · BlueOption

Institutional decisions
made with analytical judgement.

Education Intelligence brings together, in a single layer, the administrative operations, academic performance and strategic decision-making of large education providers. Own platform, applied AI and specialised consulting, with a deployment calendar.

COHORTESP-2026-Q1
INSTITUTIONRPRT-NODE
MODELSLOCAL-EU
STUDENTS4,120
HIGH PERFORMANCENORMALAT RISK
INSTITUTIONAL READOUT
Indicators ready for board presentation.
Dropout risk
14.2 /100
At-risk students
287 /4,120
Admissions efficiency
73 /100
Model confidence
86 %
ON TRACK 78%WATCH-LIST 14%AT RISK 8%
FRAMEWORK · SCOPE

A single layer connecting academic performance, operational efficiency and institutional intelligence. The transformation stops being a five-year plan and becomes a project with a calendar.

METHODOLOGY
PLAYBOOK · v2026
ROLLOUT
4-6 WK
SCOPE
3 LAYERS
INFRASTRUCTURE
EU · GDPR
ISO 27001 · GDPR · DATA IN EU · OWN MODELS · AUDIT · TRACEABILITY
02 · Institutional edge

Why Education Intelligence.

Education Intelligence delivers the analytical framework and the deliverables a board needs in order to decide on comparable data, detect risk in time and execute on a calendar.

01

A shared frame for the whole board.

We turn academic performance, attendance, programme finance and quality into comparable signals. General management, provost and finance decide on the same dashboard, not from opposing opinions.

02

Risk detected before it becomes loss.

Every student who leaves in the first term is lost revenue and an acquisition cost that can no longer be recouped. Education Intelligence identifies risk with enough margin to intervene.

03

Transformation on a calendar.

Platform deployed, playbooks applied and measurable results within quarters. The transformation stops being a strategic promise and becomes a project with deliverables and dates.

03 · The three-layer model

Operations, academic and decision. Three domains connected under a single analytical frame.

Each layer solves a specific domain and connects with the other two: operational data feeds the academic reading, and both sustain the institutional decision.

01 · OPERATIONAL LAYER

Operational efficiency

Redesign of the critical administrative processes where hidden costs and bottlenecks concentrate: admissions, records, student support and internal operations. Automation with applied AI and measurable delivery within quarters.

  • Automated validation of credentials and records
  • Automated transcripts and certificates
  • 24/7 transactional student support
  • Mass translation and subtitling
  • Automated internal HR and IT processes
PROCESSES · AUTOMATION
L01
OPERATIONAL AUTOMATION
CONTINUOUS CYCLE
02 · ACADEMIC LAYER

Academic layer

AI applied to the learning cycle and to student care. We free faculty from administrative load and raise the quality of tutoring with personalisation at scale, while keeping teaching judgement as the final authority.

  • 24/7 virtual tutor with teaching judgement
  • Micro-learning generated from recorded lectures
  • Adaptive learning paths
  • Marking with immediate, validated feedback
  • Learning analytics for teaching decisions
PACE · COMPREHENSION · ENGAGEMENT
L02
PACECOMPREH.ENGAGE.RISKTUTOR
PEDAGOGICAL SIGNALS
READING BY COHORT
03 · DECISION LAYER

Institutional intelligence

An institutional intelligence layer over academic performance, early dropout warning and exploitation of internal knowledge. Turns operational and academic data into executive dashboards for leadership and board.

  • Early dropout warning by cohort
  • Profitability analysis by programme
  • AI-driven exploitation of internal documentation
  • Executive dashboards
  • LMS-CRM-ERP interoperability audit
COHORTS · SCENARIOS
L03
BAC
SCENARIOS COMPARED
DECISION DOCUMENTED
04 · Benefits

Less uncertainty. More calendar.

We turn faculty intuition into measurable hypotheses and projects with deliverables.

01

Dropout reduced and revenue protected.

Detection of at-risk cohorts with margin to intervene. Every retention point is recurring revenue preserved.

02

Teaching time recovered.

Automation of administrative load and return of teaching time to its real function: teaching and tutoring.

03

Compress weeks of committee into days

Shared frame for leadership, provost and finance. Decisions stop being an opinion debate.

04

Reputation and regulatory compliance.

Sensitive academic data handled under EU compliance. Accreditation, internal audits and regulators with a single documented frame.

05

Turn intuition into measurable hypotheses

Every academic or strategic decision becomes a set of contrastable scenarios, not opposing opinions.

06

Academic rationale documented.

Every decision leaves an auditable trace and a shared frame to defend it before board, committee or regulator.

05 · Compliance & privacy · operating edge

Academic Big Data without exposing the student.

We build predictive models on cohorts and aggregated signals, minimising the use of identifiable personal data. The institution gains operating intelligence without opening a new regulatory front with families, students or regulators.

MINIMAL PERSONAL DATA
Prediction on aggregated signals

We work on cohorts, patterns and aggregated signals whenever the decision allows. When individual data is needed, it stays inside the institutional perimeter.

PROCESSED IN EU
Academic data sovereignty

European infrastructure, GDPR by design and an auditable trace ready for accreditation or regulator.

LESS BREACH SURFACE
Faster procurement and legal

By minimising the personal data processed, the largest source of regulatory risk is removed from the project. Legal and compliance review is substantially shorter than in a traditional integration.

What you get
06 · Diagnosis

Education Intelligence institutional diagnosis.

Full reading of the three layers in 4-6 weeks: operations, academic and institutional. Scenario comparison and a prioritised deployment plan ready for committee presentation. No commitment to continue.