IBM Education Italy

Istituto Secoli

Enterprise Knowledge Search

Fashion-design students at Istituto Secoli struggled to deepen their collection concepts because online research was shallow, algorithmically narrowed and slow to turn into reliable inspiration.

100% of all students involved in the testing acknowledged CreativIA as a valuable tool
65% of student research actively used the tool's core features
85% of students expressing satisfaction

Reported impact

Business outcome

CreativIA improved concept-development research for students, achieved strong adoption and satisfaction in testing, and gave Istituto Secoli a differentiated educational tool that strengthens its reputation for combining fashion training with technology.

  • Customer Experience
  • Productivity Improvement

Solution

Istituto Secoli and IBM Client Engineering created a proof-of-value tool called CreativIA on IBM watsonx.ai, IBM watsonx.data and IBM Cloud Code Engine. The solution supports two parts of the concept-creation workflow. First, watsonx.ai takes a student's initial sentence and expands, rephrases and enriches it so the student can explore complementary directions instead of remaining stuck in an abstract starting point. Second, a search experience uses natural-language queries over a curated database of professor-selected articles and images stored in watsonx.data, helping students find semantically relevant references rather than generic internet results. Code Engine provides the runtime for the demo environment used in student testing. The resulting architecture combines creative ideation and governed reference retrieval in one tool, giving fashion students an AI-assisted way to research, refine and broaden collection concepts without replacing their own creative judgment.

Data flow

Students enter an initial concept into watsonx.ai for expansion, then query a curated corpus in watsonx.data for relevant articles and images, and the resulting ideas and references are surfaced through the CreativIA application hosted on Code Engine.

Solution architecture

3 components · 3 layers
  1. Compute
    • IBM watsonx.ai Expands and enriches student concept prompts so designers can explore broader creative directions.
  2. Storage
    • IBM watsonx.data Stores the curated article and image corpus used by CreativIA's semantic search capability.
  3. Serving
    • IBM Cloud Code Engine Hosts the AI-powered tool and its demo environment for user testing and iterative improvement.

Architecture clues

  • IBM Client Engineering ran user testing with students to refine features and UX.
  • The initial corpus came from a single integrated website during testing.
  • The proof of value split the experience into concept expansion and semantic search over curated content.

Evidence from the source

100% of all students involved in the testing acknowledged CreativIA as a valuable tool
65% of student research actively used the tool's core features
IBM Cloud Code Engine
IBM watsonx.ai
IBM watsonx.data
Transparency Evidence & methodology 95/100 reference value · 92% 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 value95/100
  • 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 specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence92%
  • 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 provenance10/10
    The publication date comes from the source page or publisher.
  • 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. IBM

    Istituto Secoli customer story

    First-party
    https://www.ibm.com/case-studies/istituto-secoli
    Source type
    Vendor-published customer story
    Published
    Feb 7, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date
  2. Aziende.it

    Istituto Carlo Secoli S.r.l.: fatturato 2024 e P.IVA 07213070159

    Independent secondary
    https://www.aziende.it/istituto-carlo-secoli-s-r-l

    The profile lists "Dipendenti" as "27", which maps to SMB under the enrichment policy.

    Source type
    Structured company profile
    Supports
    • Company size

Date evidence

Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.