Your organisation's knowledge is spread across CMSs, PIM, CRM and document stores — and AI systems now consume all of it. Kodiac builds one structured, versioned representation across that stack, with the retrieval surface, graph and interfaces to serve it reliably.
Structure isn't a workaround for model limitations. It's how an organisation gets deterministic properties — consistency, versioning, traceability — out of a probabilistic consumption layer.
Each system in your estate is internally governed. What no system provides is a single, coherent representation of the organisation that AI consumers can retrieve from with confidence.
The same fact exists in five systems with four values. AI systems retrieve whichever they reach first. There is no canonical record to point at — for them or for you.
Unmodelled content retrieves approximately: wrong chunk, stale version, missing context. Precise retrieval needs explicit entities, relationships and attributes — a model, not a crawl.
When an AI system states something about your organisation, you should be able to trace it to a versioned, approved record — and replay exactly what was served, when, to whom.
Kodiac connects to the systems you already run, normalises their content into a governed graph of entities, relationships and claims, and exposes it through interfaces built for AI consumers.
Entities, relationships and attributes modelled explicitly, with taxonomy and schema generated from the model. Content from every connected system maps onto one structure.
POST /v1/content/retrieve — top-k retrieval with relevance scoring, filterable by category, status, locale and tag. Semantic chunking and reranking over an automatically maintained vector index. Built for production LLM grounding.
The same governed knowledge exposed to external AI systems and agents via Model Context Protocol and REST. Signed responses, per-endpoint auth, only approved records ever served.
Every record carries version history, approval state and ownership. Webhooks on record.created / updated / published, plus CI test scenarios that validate agent outputs against expected answers.
SAML 2.0 SSO, SCIM 2.0, MFA, IP allowlisting, data residency controls. Full interaction logging with 365-day retention and SIEM export.
Kodiac is not a replacement CMS and doesn't ask for one. Connectors sync incrementally from Sitecore, AEM, Contentful, WordPress, Drupal, Sanity, SharePoint, Salesforce, HubSpot and more. Your systems remain the systems of record for their domains; Kodiac maintains the governed representation across them.
Pages, feeds and agent responses all render from the same versioned knowledge — the CMS evolves into one output among several.
The shape of the integration
CMS · PIM · CRM · DAM · SharePoint · Documents
Governed knowledge graph
entities · relationships · versioned claims
AI systems · customer agents · your own applications
Phase 3 builds naturally on the structured foundations: a Brand Agent serving trusted, current answers over MCP and REST, backed by the same governed records — and instrumented like any other production service.
Walk through the architecture with us — graph, retrieval, MCP, governance — or start with the free audit to see what AI currently reconstructs from your estate.
