Wetlands and biodiversityLandscape · Wide viewEcosystem
From editorial content to a learning experience.
OLA, built for Grupo Anaya, combines editorial production, a semantic DAM and an LMS for teachers and students. AI accelerates content creation, adaptation and review; MCP connects editorial production tools.
What it makes possible
Structured activities and adapted materials that the team can review, publish and reuse.
How it takes shape.
We start with
Publisher PDFs, content and visual resources.
OLASCIENCE · FICTIONAL EXAMPLEWho produces its own food?
SunlightPlantDeer
STARTING WITH
Sunlight → plants → deer
THIS STAGE’S RESULT
Goal: recognise a food chain
Fictional example · science content
01 / 05 · Start with text
Extract structure and activities from PDFs
Editorial material and level guidance define what each proposal should cover.
Goal: recognise a food chain
OLASCIENCE · FICTIONAL EXAMPLEWho produces its own food?
SunlightPlantDeer
STARTING WITH
Goal + level + activity type
THIS STAGE’S RESULT
Identify the producer / explain the relationship
Answer: plants are the producers.
02 / 05 · Generate
Generate variants by difficulty and objective
Batch proposals support the same content through different activities.
Identify the producer / explain the relationship
OLASCIENCE · FICTIONAL EXAMPLEWho produces its own food?
SunlightPlantDeer
STARTING WITH
Activity + proposed answer
THIS STAGE’S RESULT
Consistent question · checked answer
Structure / content / answer review
03 / 05 · Check
Review answers and repair issues
Structure is validated and questions and answers are reviewed, repairing detected problems.
Consistent question · checked answer
OLASCIENCE · FICTIONAL EXAMPLEWho produces its own food?
SunlightPlantDeer
STARTING WITH
Productor → producer · Consumidor → consumer
THIS STAGE’S RESULT
Activity and labels in the target language
Fictional example · luz solar / sunlight · planta / plant · ciervo / deer
04 / 05 · Translate
Translate text and images in context
Activities and labels are translated in context for editorial review.
Activity and labels in the target language
OLATHIS STAGE’S RESULT
Real LMS screenshot · shows content in use, not AI generationIntegrated content to publish and reuse
Teams validate before publication.
05 / 05 · Integrate
Integrate resources into production workflows and the LMS
Reviewed materials are incorporated into publishing tools and the LMS for publication and use.
Integrated content to publish and reuse
Technology prepares and organises. People review and decide.1 / 5
Enlarge screenshot ↗Technology works. People move forward.
Time back for editors and production teams: less manual work, more attention to learning quality.
Educational publishersProduction and QA teamsLearning platforms
Batch generation, structural validation, review and repair are implemented. Editorial production tools compare drafts with published content and prepare changes for review.
OLA · Grupo Anaya · DAMYour visual collection.
Your visual collection.
Easier to discover.
A DAM is a digital asset repository. We make it searchable by meaning: describe the image you need and find related assets, even when you do not know the filename.
- Semantic search of images in your own collection.
- Natural-language requests converted into catalogue filters.
- Reused or adapted assets, with references to the original.
Less time searching for files or recreating assets. More time creating and making decisions.
Explore this capability ↗OLA
JPG · IllustrationQUESTION / CONTEXT
“A wetland to explain biodiversity”
THIS STAGE’S RESULT
Subject: wetland · use: educational resource
Fictional example · search within your collection
01 / 03 · Describe
Describe the image you need.
The request expresses the subject and use conditions even when the filename is unknown.
Subject: wetland · use: educational resource
OLAJPG · IllustrationSTARTING WITH
Subject + format + catalogue metadata
THIS STAGE’S RESULT
Related assets for selection
Teams check result relevance.
02 / 03 · Find
Meaning and metadata together.
Semantic search gathers related assets and natural-language requests become catalogue filters.
Related assets for selection
OLASEMANTIC DAMOne idea. The right images.
IllustrationYOUR REPOSITORYImages · Meaning and metadata
Images to explain the biodiversity of a wetland
Life below the surfaceIllustration · Editable layersFood web
From your collection to your next creationSelection · Reuse · Source reference
03 / 03 · Reuse
Assets retain their origin.
People select an asset, review its conditions and retain the original reference when reusing or adapting it.
Asset ready for editorial work
Technology prepares and organises. People review and decide.1 / 3
Content in use · Real screenshotsThe same content.
The same content.
More ways to learn.
The LMS turns educational content into a reading, practice and teaching experience. These views come from Anaya’s public demo.
Explore the Anaya demo ↗The book in a digital environment
Editorial content with navigation and reading tools.
An experience built for teaching
Teacher view, activities and access to teaching resources.
Lingua 1. Primaria. Libro dixital · Anaya. Screenshots show the LMS; editorial AI and MCP capabilities are described separately in this case.
Change the language.
Keep the resource.
The agent identifies text, translates it and reviews how it fits the image. One landscape, six processes and their arrows: the resource adapts to reach new readers.
OLATHIS STAGE’S RESULT
Workflow illustration · fictional examples, except identified evidenceEvaporación / condensación / precipitación
AI-generated illustration · fictional example
01 / 03 · Identify
First, identify the text.
Labels and their relationships to illustration elements are identified.
Evaporación / condensación / precipitación
OLASTARTING WITH
Evaporación → evaporation
THIS STAGE’S RESULT
Condensación → condensation
Precipitation / runoff / infiltration / groundwater
02 / 03 · Translate
Meaning follows each label.
Translation retains the relationship between process, label and arrow.
Condensación → condensation
OLATHIS STAGE’S RESULT
Workflow illustration · fictional examples, except identified evidenceAsset localised into English
Illustrative example; not an OLA output.
03 / 03 · Review
Same landscape, new labels.
Legibility and fit are reviewed while retaining the content, six processes and their arrows.
Asset localised into English
Technology prepares and organises. People review and decide.1 / 3
Enlarge image 
Enlarge image AI-generated illustrations showing the localisation of an educational resource. They are not OLA screenshots or pages from a commercial textbook.
Three needs, distinct capabilitiesFrom the editorial team
From the editorial team
to the classroom.
The same content foundation supports production, support and learning. Each connection has its own purpose and permissions.
Create and adapt
Batch activities, answer checks, contextual translation and image localisation. Teams validate before publication.
Production and QA
MCP for diagnosing assets, licences, issues and differences between drafts and publications. Changes prepared for review.
Teach and learn
An LMS for working with content, preparing lessons and supporting teachers and learners.
A capability that adapts to you
What about your organisation?
This project demonstrates a capability we can adapt to your organisation. Let’s explore how your knowledge can help users and become new services, licences or editions, with less repetitive work.
More value for people and your organisationYou have the knowledge.
Let’s explore your project ↗You have the knowledge.
Let’s take it further.
New uses for your content, more time for your team and opportunities to earn revenue.