Google Cloud Education The Netherlands

BeSmart Campus

BeSmart Campus needed a way to deliver individualized instruction at scale after demand for tutoring surged, but static online video could not answer questions or adapt explanations to each student's pace and understanding.

The first operational version of the BeSmart Learning Platform was designed in only three months
two classes allowed to use the platform for two weeks preceding exams achieved averages of 6.4 and 6.9 out of 10
two other classes of the same level, prepared without the platform, showed an average of 5.0

Reported impact

Business outcome

BeSmart launched its first operational platform in three months, produced measurable student gains in school tests, and created a scalable tutoring model that can re-explain concepts as many times as each learner needs.

  • Customer Experience
  • Productivity Improvement
  • Scalability
  • Speed to Market

Solution

BeSmart Campus built an interactive learning platform on Google Cloud so educational video content can be paired with real-time AI tutoring instead of passive playback. The company uses Gemini models to analyze and organize teacher-created video lessons, then relies on multimodal understanding to let students pause a lesson at any moment, ask a question about the exact point on screen, and receive an explanation that follows BeSmart's own pedagogical method. Vertex AI and Gemini supply the reasoning layer, while BigQuery supports the data foundation behind the platform's evolving content and results. The system also generates practice exercises on the fly and uses the same course context to explain mistakes, rephrase concepts repeatedly, and guide students through alternative examples. This architecture turns the platform into a personalized tutor that can keep pace with each learner while staying inside a controlled instructional environment.

Data flow

Teacher-created videos are analyzed and organized with Gemini, students watch those lessons in the BeSmart platform, pause them to ask context-specific questions, and receive grounded responses or generated exercises that stay tied to the exact lesson segment and teaching method.

Solution architecture

4 components · 3 layers
  1. Compute
    • Vertex AI Hosts the AI capabilities used to power contextual tutoring across BeSmart's learning platform.
    • Gemini Models Interpret video context and generate explanations, rephrasings, and practice exercises for students.
  2. Storage
    • BigQuery Supports the platform's data layer for educational content and outcome analysis.
  3. Orchestration
    • NotebookLM Helped validate that Gemini could understand educational content with the needed contextual fidelity.

Architecture clues

  • Students can pause videos and ask questions tied to the exact moment in the lesson.
  • The AI generates practice exercises in real time and guides correction.
  • The company designed the first operational version in three months using Google's orchestration, processing, and AI integration capabilities.
  • The platform relies on video grounding so Gemini answers stay consistent with BeSmart's controlled corpus.

Evidence from the source

Dutch EdTech company BeSmart Campus leverages Google Cloud and Gemini models to offer every student a personalized AI tutor, directly integrated into educational content designed with teachers.
Thanks to its multimodal understanding, Gemini immediately identifies the relevant section and provides a response consistent with the pedagogical method designed by BeSmart Campus.
The AI never gets impatient and can rephrase ten, twenty, or thirty times if necessary.
The first operational version of the BeSmart Learning Platform was designed in only three months
two classes allowed to use the platform for two weeks preceding exams achieved averages of 6.4 and 6.9 out of 10, while two other classes of the same level, prepared without the platform, showed an average of 5.0
Transparency Evidence & methodology 86/100 reference value · 82% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value86/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence82%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency9/10
    2 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Google Cloud

    BeSmart Campus customer story

    First-party
    https://cloud.google.com/customers/besmart
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
  2. LinkedIn

    BeSmart Campus | LinkedIn

    Independent secondary
    https://www.linkedin.com/company/besmartcampus/

    The Organization JSON-LD lists numberOfEmployees value 13, and sameAs 'http://www.besmartcampus.com'.

    Source type
    Structured company profile
    Supports
    • Company size

Date evidence

  • First archived Feb 16, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jan 15, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.