--- title: Loredex description: >- Loredex is a headless knowledge back end: a virtual file system with folder-level access control, a publishing flow, a concept index and context graph, health scores, and MCP and REST APIs. Start in Loredex Cloud, deploy locally when you need to. url: 'https://www.intentface.com/loredex' publisher: Intentface --- # Loredex > The knowledge back end for agents and the people they work with. **Knowledge needs a back end.** Loredex is the knowledge layer underneath Intentface OS and Intentface Studio: a virtual file system with real access control, a publishing flow, an index of your team's vocabulary, and agents that keep all of it current. Headless primitives over MCP and a REST API. ## One knowledge layer, three ways in Loredex holds the knowledge and the rules about it. Everything above it is a surface, including ours. - **Loredex**: The back end: files, folders, permissions, the index, the graph, the maintenance agents. Ships with a default UI, and exposes every primitive if you would rather build your own. - **[Intentface OS](https://www.intentface.com/os)**: Loredex plus the extensions around it: the Slackbot, the app in your pocket, brand templates, platform agents, presentations. The full product, for a whole organisation. - **[Intentface Studio](https://www.intentface.com/studio)**: The place agentic experiences get built and run. Studio reads from the same Loredex workspace, so an agent you ship inherits the knowledge your team already curated. ## Files and folders, with permissions that mean something A workspace is a folder tree, not a proprietary blob store. Markdown stays markdown, structured data stays queryable, and the whole thing survives export, import and any database underneath it. - **Folders are the access boundary**: A folder decides which people and which agents can read it and write to it. Every file inside inherits the answer, and an API key can be pinned to one branch of the tree. - **Three native types**: Markdown documents, SQLite tables, and sandboxed React views over those tables. To a person a table is a table; to an agent it is a database it queries with SQL. - **PDFs and images read on arrival**: Contracts, decks and whiteboard photos are extracted into text and indexed the moment they land, so they answer questions like any other file. ### Native file types - **Markdown**: Real files: prose, guides, meeting notes. Portable, diff-able, fully versioned, and written in a rich editor that leaves the file clean. - **Database**: Tables for the data that never sat well in prose: deals, hours, inventory. Row-level changelog, named save points, SQL for agents. - **View**: A sandboxed React page over one or more tables: a dashboard, a report, a small interactive app, styled with the workspace's own tokens. ## Nothing becomes truth until someone publishes it A document an agent will quote as policy should not change because somebody has edit access. Loredex separates what is being worked on from what is being relied on, and records every step either way. - **Full history, portable**: Documents keep restorable versions, tables keep a row-level changelog, and a workspace-wide audit trail logs which tool ran, on what, by whom. All of it survives export and re-import. - **Scoped API keys**: Hand a narrow slice of the workspace to an external agent or integration: folder-pinned, expiring, shown once and stored only as a hash. ## Four deterministic routes to the same file Retrieval that can explain itself. A folder's table of contents to orient, a dictionary in your team's vocabulary, a graph built from mentions, and search that resolves terms before it ranks anything. No vector guess sitting between a question and its answer. - **Table of contents & authored facts**: Every folder carries a generated toc.md with a line per file, plus facts people and agents write by hand. It is the first thing an agent reads. When a change outdates a fact, a human validates before anything is rewritten. - **The dictionary**: As files are saved, Loredex builds a back-of-the-book index of what they are about: canonical names in your team's vocabulary, aliases, scope notes, and every place a concept appears. Human edits are law; the rest maintains itself. - **The context graph**: Under the files sits a graph of people, files and concepts, built from every @mention, backlink and see-also. Related ideas stay one hop apart, so an agent follows edges instead of guessing filenames. - **Search that reads the query**: Every team has its own words: codenames, ticket prefixes, terms that mean something specific here. Search consults the dictionary first, expands the query to every alias, and only then runs full-text. Agents get the same route through concept_resolve. ## Built to be maintained by agents Knowledge bases rot when upkeep depends on people remembering to do it. Loredex makes the upkeep addressable: gaps are reported into the system as work, and scheduled agents pick that work up overnight. - **Agents file the gaps**: When a search comes up empty or two documents contradict each other, the agent does not shrug. It files a content gap or an outdated page through submit_feedback, with the failed query attached. - **Overnight passes do the chores**: Scheduled agents merge twin concepts, split overgrown ones, let one-off noise go dormant, backfill scope notes, and draft the pages that keep coming up missing. - **Suggest, then dispose**: Maintenance never deletes and never reverts a human edit. It proposes, a person clicks yes or no, and the decision is recorded. Roughly 90% machine, 10% human, and that 10% is veto power rather than workload. - **Health scores with evidence**: Structure, search, context quality and activity each score 0 to 100. The composite says what is dragging, the evidence is one click away, and every search and read feeds it. ## A knowledge base should not be an island Loredex does not have to contain everything. It has to know where everything is. Mount external sources into the index, sync live systems into local tables, and let a concept point at the tool that actually does the job. - **Mounted, not copied**: Articles in a GitHub repo, marketing pages, a partner wiki: external sources mount straight into the tree and the search index. The content stays where it is authored; agents read it like a native file. - **Synced, not fetched**: Sandboxed pipelines pull live systems into local read-only tables: fast, rate-limit-proof, and when a provider changes, exactly one pipeline needs repair. Pipeline code never sees credentials. - **An index of skills**: Beyond facts, the index covers how things get done and where the pieces live. An agent asking how a release gets published gets the runbook, the repo and the right connector rather than a guess. Connectors: Slack, Clockify, Zero CRM, Circleback, Perplexity. External mounts, webhooks, and more. ## Primitives first, interface optional Every capability on this page is reachable over MCP and a documented REST API. The UI is one consumer of those primitives, and you can swap it. - **MCP for AI clients**: Claude Desktop, Claude Code, or any MCP client. A connecting agent calls orient and gets the workspace map, file outlines and the vocabulary before it reads a single document. - **Scoped REST API**: An OpenAPI spec and scoped keys behind every primitive: files, folders, permissions, the index, the graph, the health scores. Build your own agents, pipelines or front end. - **Ships with a default UI**: Loredex comes with its own interface and component set. Install it, start writing, and never touch the API if you have no reason to. - **Or build your own view**: Intentface UI gives you the elements to assemble a custom view of the knowledge base: trees, readers, index browsers, search. Your product's chrome over Loredex's primitives. ## Start in the cloud, move when you need to The same Loredex either way. Begin where there is nothing to run, and take it in-house the day a policy, a regulator or a security review says so. - **Loredex Cloud**: Sign in and start building your knowledge repository. Nothing to deploy, connectors and scheduled agents included, and a workspace exports whole. - **Local deploy**: Install Loredex on your own hardware or your own cloud. Same primitives, same MCP and API surface, your data never leaving your perimeter. ## Knowledge is infrastructure. Give it a back end that treats it that way. Loredex runs on its own, under Intentface OS, and behind the agents built in Intentface Studio. Wherever you start, it is the same workspace. [Request early access](https://www.intentface.com/contact)