Alot Labs
Menu
Work
Deployments Lab Live Writing
Firm
About Capabilities Services Method Pricing Careers The commitment Compare the alternatives Book the briefing
← All deployments
Case study · Deployment 06

corpus

One place for everything a team needs to remember or ask again later: chat, structured memory, notes, bookmarks, documents — and a knowledge search that spans all of it.

Knowledge workspace Retrieval across sources Structured memory Document inbox
TypeTeam knowledge workspace StatusIn production — run at our own expense StackTypeScript · Express · Postgres · React Runs inSelf-hosted today · your VPC on engagement
The problem

Institutional knowledge dies in five places at once: a chat thread, a note nobody can find, a bookmark saved and forgotten, a document in someone's inbox, and a decision that lives only in a colleague's head. The answers exist; retrieval is what is broken. corpus is the retrieval layer: one workspace where knowledge lands, gets structure, and can be asked a question.

5
places knowledge normally dies — chat, memory, notes, bookmarks, documents — living as one workspace
1
search that spans all of them — a question, not five apps to check
1
generated schema shared by every surface — chat, search, and stores cannot drift
100%
of answers traceable to the store they came from — retrieval you can check
What it does
01
Capture everything in one place

Markdown notes, bookmarks, a document inbox for files that need a home, and chat — all first-class citizens of the same workspace instead of five disconnected apps.

02
Give memory a structure

Knowledge is organized the way people actually remember — a memory palace of wings, rooms, and items — so related knowledge lives together and browsing works when you don't know the keyword.

03
Ask instead of hunt

Knowledge search runs across every store at once — notes, memory, bookmarks, documents, chat history. The question “what did we decide about X?” gets an answer, not a list of folders to check.

04
Chat that knows the workspace

The conversational surface answers from what the workspace holds — retrieval-augmented, grounded in a store the team controls.

Stack: TypeScript monorepo — Express API over Postgres with a typed ORM, OpenAPI-generated schemas and hooks shared by every surface, React + Vite front end.

Architecture
5 STORES — WHERE KNOWLEDGE USED TO DIE Chat conversations kept Memory structured facts Notes markdown, first-class Bookmarks saved, not forgotten Documents an inbox with a home One workspace — Postgres, one generated schema wings · rooms · items — human-legible structure, so browsing works when keywords fail Knowledge search one query spans all 5 stores at once “What did we decide about X?” a question, in plain language The answer, with its source not a list of folders to check
The decisions that matter
Structure beats a pile of embeddings

Dumping everything into a vector store is the default RAG failure mode: when the embedding misses, the user gets nothing. corpus keeps human-legible structure — wings, rooms and items, collections, the inbox — and layers search over it, so retrieval degrades into browsing rather than a dead end. That structure also lets every answer point back to where it came from.

5 stores were the requirement, 1 search was the product

Teams genuinely produce all five kinds of knowledge, so chat, memory, notes, bookmarks, and documents each needed to exist. The decision was refusing to let them stay silos: every store lands in the same schema, which makes one question searchable across all of them at once.

One schema, every surface

Types and client hooks are generated from the single API contract, so the chat surface, the search, and the stores cannot silently disagree about the shape of knowledge.

In production

Chat, memory, notes, bookmarks, documents and cross-store search running as one workspace — built and operated by us as the place our own knowledge lives.

What we would deploy for you

The workspace pointed at your team's knowledge — wikis, decisions, documents, links — running in your infrastructure, with retrieval your people can trust because every answer shows its source.

Related deployments
Book the briefing Send the workflow