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Knowledge Base

Capturing research and exploring what you know — action phrases, the Knowledge Hub, and your knowledge graph.

4. Saving Research with Action Phrases

Action phrases are short commands you type in Chat to save and update articles without leaving the conversation. ENGRAM recognizes them automatically, drafts the content using your configured AI model, and shows a pill on the message confirming what happened.

4.1 The three commands

Create an article — drafts a new article from your current conversation:

create article: Comparing vector databases for RAG

You'll see a green Article saved pill when it's done.

Update an article — finds the article you mean and creates a new, superseding version:

update article: add a section on hybrid search trade-offs

You'll see an amber Article updated pill. Because articles are versioned, an update never destroys the previous version — it's preserved in the article's history.

Save the last response — captures the assistant's most recent response as an article:

save as article: [<title>]

The title is optional — if you leave it out, ENGRAM picks one. Handy when the answer you just got is itself the thing worth keeping.

4.2 Choosing a source with :from:

By default, create and update draw from your conversation, and save as article draws from the last response. You can point a command at a different source with a :from: suffix: 

create article: Tavily vs. SerpAPI :from: web

Available sources:

4.3 Finding the article afterward

Saved articles appear in your Library on the Knowledge Base tab. They're private by default. When an article later informs a chat answer, you'll see a blue Referenced pill linking back to it.

4.4 Natural language also works

You don't have to memorize the exact syntax. ENGRAM also recognizes natural requests like "create a report about X" or "update the article with Y" — the canonical phrases above are just the most reliable way to be explicit about what you want.

5. The Knowledge Hub: Articles and Documents

The Knowledge Hub is the heart of ENGRAM — where your research stops being disposable chat and becomes a durable, structured knowledge base. It holds two kinds of content: articles and documents, both browsable in the Library on the Knowledge Base tab.

5.1 Articles

An article is a structured markdown document — a comparison, an architecture analysis, a literature review, a how-to, a decision record. Unlike a chat message, an article is a first-class entity in your knowledge graph: it's split into sections and passages, its key concepts are extracted as entities, and it participates in retrieval alongside your memories.

5.2 Documents

A document is a file you upload — a PDF, a markdown file, or plain text — that you want ENGRAM to read and index. Like articles, documents are split into passages, entity-linked, and retrievable. Use documents for source material you didn't write yourself but want to reference: a paper, a spec, a report. Documents are also private by default.

5.3 Public vs. private

Both articles and documents carry a visibility setting: private or public.

Publishing is a deliberate, one-way action: you can make private content public, but you cannot un-publish it. Make something public only when you're sure you want to share it.

5.4 The Library

The Library (on the Knowledge Base tab) lists your articles and documents with type badges so you can tell them apart at a glance. From here you can open an article to read it, view the entities it mentions, see its version, and toggle its visibility.

5.5 How content gets in

You add content to your knowledge base by:

See §4 Saving Research with Action Phrases and §9 Connecting External Tools for the full workflows.

6. Exploring Your Knowledge Graph

Beyond reading individual articles, ENGRAM lets you see your knowledge as a connected whole. The Graph Explorer on the Knowledge Base tab turns your articles, documents, and the entities they mention into a navigable map of your topics.

6.1 Why a graph view

A list of articles tells you what you have; a graph tells you how it fits together. The Graph Explorer reveals clusters of related work, the concepts that bridge them, and the corners of your knowledge that are thin. It's the fastest way to rediscover something you half-remember and to see the shape of what you know.

6.2 Three ways to look

6.3 The topic map

The Overview topic map is generated for you — ENGRAM clusters your knowledge into labeled topics so you don't have to organize anything by hand. As your knowledge base grows, you can refresh the topics to recompute the clusters, and you can rename any topic to a label that makes sense to you; your custom labels are preserved across refreshes. A topic map needs some content to be meaningful — early on it may be sparse, and it becomes genuinely useful once you've saved a handful of articles and had a few research conversations.

6.4 Coverage and gaps

The Analytics tab complements the graph with a coverage view: which entity types and topics you've covered well, where the gaps are, your most-referenced entities, and recent activity. Use it to spot areas worth researching next.