Most enterprise content isn't structured for retrieval — no metadata, no clean chunks, no consistent taxonomy. We turn your existing content, whatever format it lives in, into a knowledge layer that LLMs can actually use.
of enterprise content is effectively invisible to AI systems.
Your knowledge is spread across help centers, wikis, PDFs, product docs, DITA, Word, and legacy publishing tools. No retrieval pipeline can cleanly ingest that mix as-is.
Without consistent chunking, frontmatter, and taxonomy, AI assistants retrieve the wrong passages — or hallucinate.
Teams can't tell which content is AI-ready and which will quietly degrade the quality of every answer.
Pick a source format to see the same transformation we run at scale — raw, unstructured content becoming retrieval-ready structured output with metadata and clean chunks.
Illustrative examples. Real migrations run thousands of topics through the same validated pipeline.
Whatever your content is in today, we make it AI-ready. Start with an audit to see where you stand, or go straight to a full migration. Built for enterprises, scale-ups, product teams, and support orgs — any team whose knowledge needs to work with AI.
Know exactly where your content stands — in any format — before committing to a migration.
Any source format, converted to a structured, retrieval-ready knowledge layer.
A full retrieval system, from migration to a live, evaluated content pipeline.
All engagements are fixed-scope. Final pricing depends on content volume and source complexity — discussed transparently on a discovery call.
We're format-agnostic by design. If your content can be exported or accessed, we can make it AI-ready — and deliver it into whatever pipeline or assistant you run.
Don't see your format or tool? If it holds content, we can handle it. Ask on a call.
No account managers, no offshore handoffs, no black box. You work directly with someone who has spent 14 years inside enterprise content systems and builds the pipeline that migrates your content.
One validated pipeline handles any source. You are not paying us to learn your format from scratch — we have already solved the hard parsing problems.
Every engagement ends with measurable retrieval scores, not a promise. You get proof your content will actually perform in an AI system.
The migrated content, the pipeline, and the documentation are yours in your own Git repo. No lock-in, no proprietary platform you have to keep paying for.
Every migration follows the same validated process. You see and approve the output before we scale it.
We walk through your content system, export the topic list, and agree on scope and acceptance criteria.
→ signed scope + topic inventoryWe configure the parser for your source format and migrate a small sample batch for your sign-off before the full run.
→ sample batch + approvalWe run the full pipeline with embedding-based deduplication and a review queue for edge cases.
→ complete structured corpus in GitWe score chunk coherence, metadata completeness, and retrieval quality, then flag anything below threshold.
→ validation report + scored topicsWe set up your build pipeline, document everything, and support your team through the transition.
→ live pipeline + documentationAnswer four quick questions for an instant readiness score and a recommendation on where to start.
An enterprise data-platform company needed its product documentation moved off a legacy publishing system and made ready for an AI assistant.
The existing documentation was generated by a legacy HTML publishing tool — nested tables, inline styling, and no consistent metadata. We built a custom parser to migrate the full corpus to structured Markdown, added YAML frontmatter to every topic, ran embedding-based deduplication, and validated the result against a retrieval-quality benchmark before handover.
Details anonymized. The same pipeline applies whether your content lives in a legacy publishing tool, a help center, a wiki, or a mix of all three. Full walkthrough available under NDA on a discovery call.
14 years designing enterprise content systems, including information architecture and AI-content work at Adobe and Actian. Knowlayer is built on a simple belief: the companies that win the AI era will be the ones whose knowledge is structured well enough for both humans and machines to depend on. Every engagement is delivered hands-on, by the person who built the pipeline.
Book a 30-minute discovery call. We'll look at your content, talk through the gaps, and tell you honestly whether an audit or a full migration makes sense.
We'll be in touch within one business day to set up your call.