Entities
- Corpus
- Content item
- Creator or publisher
- Version and date
- Permission and audience
- Topic, entity and metadata
- Query or information need
- Retrieved passage
- Result or synthesis
- Citation and coverage
- Recommendation
- Feedback and action
Content, Knowledge and Discovery
Content, Knowledge and Discovery Platforms
Content and knowledge products help people find, understand, compare and act on material they did not create in the current moment. Search quality matters, but ranking alone cannot explain what is in the corpus, who may access it, which version is authoritative or whether a generated synthesis covers the evidence required for the decision.
The corpus changes the product
Different products organise different knowledge contracts:
- 01
Publishing and media products
Balance timeliness, editorial structure, identity and audience journeys.
- 02
Research and scientific platforms
Require precise metadata, versions, methods and citation paths.
- 03
Organisational knowledge products
Inherit permissions, ownership and changing source systems.
- 04
Learning libraries
Connect discovery to sequence, practice and progress.
- 05
Developer documentation
Connects concepts, examples, versions and executable work.
- 06
AI retrieval products
Create a new synthesis layer whose source coverage must remain inspectable.
The team must decide what counts as a document, passage, version, collection, topic, source and recommendation before it can judge whether search is good.
From corpus to action without losing provenance
Knowledge discovery and provenance contract
Show how a result or synthesis inherits access, identity and version from its sources.
Relationships
- Corpus scope and permission determine eligible items.
- Query and metadata retrieve passages from identified versions.
- A synthesis cites the passages supporting each consequential claim.
- Coverage distinguishes available evidence from missing evidence.
- A recommendation names the objective and action it supports.
- Feedback improves retrieval without silently changing source history.
Search, browse and recommendation serve different intent
Search helps when a person can express what they need. Browse helps when they need to understand the available space. Recommendation helps when the product uses context and an objective to bring something forward.
A useful experience can combine them without presenting every route as one search box. It should preserve:
- what the system searched;
- how filters changed eligibility;
- why a result or recommendation appeared;
- which source and version the result represents;
- what the person can preview before committing;
- how feedback changes later discovery.
In the Eden AI case, Tcules brought template discovery, AI assistance and from-scratch workflow creation into one entry model while preserving their distinct modes. Preview and documentation access kept technical context near selection.
AI reduces reading cost and adds a coverage problem
Summaries, answer generation and conversational retrieval can help someone move through a large corpus. They can also compress disagreement, omit relevant sources or present a partial answer with the tone of a complete one.
The product should expose source coverage, permission and version where they affect the decision. For high-consequence use, citation must connect the claim to the passage rather than only provide a list of documents. Correction and feedback should not rewrite the underlying source.
The W3C PROV-O recommendation (opens in a new tab) provides one formal vocabulary for representing provenance. Tcules uses standards according to the product context and does not imply that every content platform needs that implementation.
How the work comes together
Tcules can combine corpus and object modelling, information architecture, metadata and taxonomy, search and recommendation UX, AI evidence and control, responsive reading, design systems, frontend and backend delivery, APIs and integrations.
Portfolio records include Ringier and JoVE, but their exact product responsibility and public rights are not yet established. They remain private evidence opportunities. The public proof on this page is limited to Eden AI's workflow discovery and The Wandering Raven's learning-content and Moodle implementation context.
Bring the corpus the person's decision and one difficult result
Bring the corpus, the person's decision and one result that is currently difficult to trust or act on. That is enough to locate the discovery problem.