Legacy SaaS dossier · notion

Notion

CategoryWiki / docs / loose tasksNotion Business + Notion AISite ↗

A markdown wiki with a database overlay, sold per-seat with an AI add-on that's a Claude call you're already paying for.

01 · Data

Data the SaaS sits on

Markdown + GitYours

Okta / Google SSOYours

S3 (attachments)Yours

Internal Build Score

0.78

Feasibility of a useful internal substitute for the actually-used 20% of this SaaS, built with Claude and your own data layer.

IBS = 0.25·U + 0.25·C + 0.20·D + 0.15·I + 0.15·Mthis record · 78%

U
User adoption gap
weight 0.250.70
How much licensed surface area sits idle.
C
Core simplicity
weight 0.250.90
How small the actually-used 20% is when re-implemented honestly.
D
Data portability
weight 0.200.78
How clean the exit is, exports, formats, audit lock.
I
Integration burden (inverse)
weight 0.150.70
How few external systems must keep working through the SaaS.
M
Moat erosion
weight 0.150.82
How much the original differentiator has been commoditised by LLMs + cheap infra.

Editorial heuristic. Not investment advice, not a procurement recommendation.

03 · Feature usage

Commonly used vs. rarely touched

Commonly used

Hierarchical pages with blocks
Linked databases for projects + docs
Comment threads + mentions
Search across the workspace
Per-page permissions

Rarely touched

Notion AI sold as a separate per-seat upsell over the LLM you already pay for
Forms / Mail / Calendar, acquisitions stapled to the page tree
Sites / Public publishing, a half-built CMS
Automations every team rebuilds three times before giving up
Whiteboards, charts, sub-databases, formulas, depth no one finishes learning
API rate limits that punish anyone actually building on it

Build it yourself→

Internal build

Build it yourself

01 · Stack & flow

Postgres

Next.js

Claude API

Markdown + Git

Internal build map

Data in

Markdown repo

Directory ACL

Attachments

Agent layer

Tsvector index

/ask agent

Logic

scope to ACL

retrieve passages

cite page + heading

@-mention notify

Outputs

Rendered page

/ask answer

Comment thread

Build time: 4 weeks
Run cost: $2/seat·mo
vs. SaaS: $24K / yr

Build outline

Markdown repo per workspace, Git-backed
Next.js renderer with Postgres tsvector search
Claude /ask endpoint over the indexed corpus
Per-folder permissions via directory ACL
Comment + mention service in ~200 LOC

02 · Build it

Paste into Cursor or Claude Code in an empty repo. It scaffolds the working core, with the AI step embedded.

Build prompt · Notion

// Build: internal wiki (Notion replacement) # Paste into Cursor or Claude Code in an empty repo. Build an internal wiki covering the part of Notion we use: nested pages, linked databases, search, comments, and an /ask over your own docs. Ship a working v1. Stack: Next.js + Postgres (Drizzle, tsvector search) + Markdown in Git + Okta/Google SSO + Claude. Build, in order: 1. Pages as Markdown in a Git-backed repo; render with a tree nav. 2. Full-text search via Postgres tsvector. 3. Per-folder permissions from directory (Okta) groups. 4. Comments + @-mentions. 5. AI /ask over the indexed corpus, scoped to the user's access: """ Answer using ONLY pages the requester can read (ACL passed in). Cite every claim with page title + heading. If two pages disagree, show both with last-edited dates. <=120 words, answer first then sources, no filler. If you lack access or context, say so; never fabricate a reference. """ Skip: the per-seat AI tier, Sites/CMS, the half-finished automations. Done when: a teammate searches the wiki and asks a question that answers with citations, respecting their access.

03 · Result

What's our incident comms SLA?

runbooks/on-call/incident-comms.md

30 min internal Slack, 4 h external status page, Runbooks › On-call › Incident comms

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