Loredex

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.

Where it sits

One knowledge layer, three ways in

Loredex holds the knowledge and the rules about it. Everything above it is a surface, including ours.

Surfaces
Intentface OS
Slackbot, mobile app, brand templates, platform agents
Intentface Studio
Agentic experiences built, shipped and traced
MCP · REST API
LoredexKnowledge layer
  • Files & folders
  • Access control
  • Publishing
  • Dictionary
  • Context graph
  • Health scores
  • Maintenance agents
  • Connectors
  • 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

    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

    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.

Virtual file system

toc.md
Clients
toc.md
Atlas & Co
toc.md
meeting-notes.md
deals.db
contract-2026.pdf
Operations
toc.md
hours-2026.db
hours-dashboard.tsx
whiteboard-q3.jpg
StrategyShared only to:Sara L., Jonas B., Mikko R.
toc.md
roadmap.md
vendor-eval-2024.md

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.

pricing.md

Pricing

Discounts

Markdown

Real files: prose, guides, meeting notes. Portable, diff-able, fully versioned, and written in a rich editor that leaves the file clean.

deals.db
dealstagevalue
Atlas & CoWon12k
Beacon LtdProposal8k
Citrus LabsLead4k
SELECT stage, sum(value) FROM deals

Database

Tables for the data that never sat well in prose: deals, hours, inventory. Row-level changelog, named save points, SQL for agents.

dashboard.tsx
48kwon this quarter

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.

Truth layer

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.

Anyone edits

Agents read it as is

Live mode

The file is what agents read, as it is right now. Every edit by a person or an agent lands immediately. Right for notes, logs and working documents.

Anyone drafts

Owner publishes

Agents read the published copy

Published documents

People and agents contribute to a draft, but agents only read the published version. Nothing changes for them until an owner publishes. Right for pricing, policies and anything an agent will quote as truth.

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.

Smart indexing

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.

Clients/toc.md
  • Atlas & Co/Notes, deals, and the 2026 contract
  • Beacon Ltd/Proposal in progress
  • kickoff-checklist.mdWhat to set up before day one

Billing

  • Invoices go out on the 1st, net 30terms.md
  • Discounts above 15% need a founder's sign-offpricing.md

Renewals

  • Atlas & Co renews in March 2027contract-2026.pdf
  • Beacon Ltd is on a pilot until Q1proposal.md

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.

O
onboardingHow a new client goes from signed to live
Onboarding revampThe 2026 rebuild of client signup
on-callWho answers, and when
P
pricingPlans, tiers, and discount policy
R
runbookStep-by-step operational procedures
renewalno scope note yet

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.

mentionslinks tobacklinkaboutsee alsoclient-onboarding.mdSara Kimpricing.mdkickoff-checklist.mdonboardingrenewal

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(“Halo”)
HaloOnboarding revamp
  • Product/onboarding-revamp-spec.md
  • Meetings/2026-08-14-steering.md
  • Ops/rollout.db

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.

Agentic maintenance

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.

Janitor agentnightly run

Reading /changes since yesterday

5 files changed

1 / 4

Good morning, Mike

Nothing new yet.

Pulse — workspace healthlast 30 days
71

Search is dragging the score down.

Search42Context83Activity100Structure100

Flagged by agents, tended by agents

content gap2h ago

Searched “parental leave policy”, got nothing — the handbook never covers it.

Workspace agent drafted parental-leave.md — waiting on a publisher.draft ready
outdated1d ago

pricing.md still lists last year's rates next to the new plans.

Superseded the old page and linked it to current pricing.resolved
hard to find3d ago

Took four searches to land on the security overview — no synonyms on the concept.

Added “SOC 2” and “compliance” as synonyms on security.resolved

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.

Connectors

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.

asksmountedsyncedpoints toyour agentdocs/*.mdxdeals.dbskill: publish a release

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.

  • Slack
  • Clockify
  • Zero CRM
  • Circleback
  • Perplexity
  • External mounts, webhooks, and more

Headless by default

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.

What did we agree about events yesterday?

Let me search your knowledge base for the past meeting notes.

search

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.

GET/v1/search?q=discount
ifk_…3f9a · scope: Company/
200 OK· 3 results · 38 ms
→ pricing.md

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.

Deployment

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.