Transform existing knowledge for your next platform without direct system connections for supported file-based workflows or manual article-by-article reformatting. Bring your source files and target requirements; iluva guides mapping, transformation and validation without rewriting or inventing your original content.
Your knowledge. Unchanged. Just transformed.
Try iluva Beta — 50 free items →Some migration solutions move data through direct connections between supported platforms. iluva focuses on a different part of the journey: transforming exported knowledge into the structure required by your chosen destination, without needing a direct system connection for supported file-based workflows.
| Connector-based migration | iluva's approach |
|---|---|
| Connect source and destination systems | Upload exported source knowledge and target requirements |
| May require API credentials and permissions | No direct system integration required for supported file-based workflows |
| Depends on supported connectors and adapters | Works from supported source and target formats |
| Platform changes can require connector maintenance | Focuses on file structures and transformation rules |
| Often handles end-to-end data transfer | Produces validated, target-ready outputs for import |
Both approaches have their place. Connector-based tools may automate extraction and loading; iluva's file-based workflow requires customers to export their source content and import the resulting files. Compatibility and preservation depend on the actual source files and target requirements.
No direct system integration required for supported file-based workflows. Your knowledge. Unchanged. Just transformed.
iluva's engine is designed to interpret source and target evidence, propose mappings, transform content and surface validation issues. Its intelligence supports the workflow without requiring users to understand the underlying technical complexity.
Knowledge managers and business owners get plain-language guidance and a self-service journey. Technical teams can supply detailed target examples, schemas and specifications and review the resulting structure. One workflow serves both audiences.
From preparing files to reviewing output, iluva is designed to explain what is needed, what happens next and how to resolve exceptions. The goal is to make every step understandable, not to leave users guessing or deciphering technical errors.
Reduce repetitive manual article-by-article reformatting through reusable mappings and guided processing. Review and validation remain important; actual processing times depend on file complexity, volume and target requirements.
The standard self-service journey is designed to be accessible without coding or specialist migration knowledge. Clear steps guide users through source uploads, target examples, mapping review, validation and download, while technical users can work with the underlying target specifications.
Work from source material and target specifications, not a fixed pair of vendor platforms. ServiceNow, Salesforce, Zendesk, Confluence, SharePoint and custom repositories are examples of migration contexts, not platform restrictions or guaranteed native integrations.
Bring real target JSON/XML examples, schemas or specifications. The transformation workflow is guided by what your destination actually requires rather than forcing articles into a generic template.
iluva does not create, rewrite, paraphrase, summarize, embellish or invent article content. It transforms the structure and representation needed by the destination while preserving the original wording and factual content. If required information is missing or unclear, iluva surfaces an exception for the customer rather than guessing. Formatting and structural changes are distinct from editing what an article says.
Article bodies are more than rows and columns. Tables, lists, images, attachments, hyperlinks and metadata matter. iluva's evaluation workflow includes checks for these elements, with preservation assessed against the actual source and target formats.
Missing target fields, unresolved references and broken links should be surfaced for review. If an article links to another document that was not supplied, the next action is to provide that document; invalid links should not simply disappear without confirmation.
Knowledge teams can start with their own files, target examples, mapping review and output validation. The experience is designed to tell users what to do next at each stage, with support available through Ask Ted if needed. A small real-data trial helps determine fit before a larger migration.
General-purpose data mapping tools may be useful for structured fields, while migration services may focus on moving records between specific systems. iluva's focus is the article-level work in between: turning existing knowledge into the target's required content structure, while preserving source evidence and making exceptions reviewable.
This describes iluva's product focus, not a claim that competing products cannot perform similar tasks or that iluva has been independently benchmarked against them.
Beta: Up to 50 free knowledge Processing Items, subject to program terms. Paid processing is disabled during Beta.
Register for the Beta →For project-specific support, sign in and use Ask Ted so questions and resolutions remain linked to a support ticket.
The story behind iluva · Product capabilities · Migration workflow · Frequently asked questions
