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AI/Productprivate client

Cleverseed

AI-powered content editing platform. We built a fully custom rich-text editor with contextual AI actions available inline as writers work.

Sector
Content tooling
Engagement
Build — core product surface
Timeline
Apr 2025 → Nov 2025
Team
2 frontend engineers
01 — The problem

Writers were being asked to leave the page to get help with the page.

Cleverseed's first version wrapped a third-party editor and put AI in a right-hand panel. Every improvement was a three-step manoeuvre: select the text, move to the panel, paste the result back. Session recordings showed writers abandoning the panel entirely and doing the work in a separate tab.

The wrapped editor also fought back. Custom marks could not be added without patching around the vendor's schema, AI suggestions could not be rendered inline, and each new feature took longer to ship than the last. The team asked us to decide whether to keep extending it or replace it, and to do whichever we recommended.

02 — How we solved it

What we built, and why in that order

01
Own the editor
We rebuilt on Tiptap with a schema Cleverseed controls. Every AI construct — suggestion, diff, generated block — is a typed node in that schema rather than a decoration layered on top.
02
Actions where the cursor is
Rewrite, Simplify and Emojify run from the selection itself. Output arrives as a reviewable inline diff the writer accepts or rejects; nothing is applied silently.
03
Generation inside the flow
Writers generate a paragraph or section at the cursor with surrounding document context passed to the model, so new text matches the voice already on the page.
04
Extension architecture
A typed extension pattern with documented boundaries means the client's team adds AI actions without touching editor internals — the first two after handover shipped without us.
StackTiptapReactNext.jsTypeScriptLLM APIs
Outcome
3 → 1
Steps to apply an AI edit
4.1×
AI actions used per writing session
0
Vendor patches in the new editor
9 days
Rebuild to feature parity
Owning the schema was the unglamorous decision that unblocked everything else. We ship features now instead of workarounds.
CTO, Cleverseed
03 — Where they are now

The editor is now the product's differentiator rather than its bottleneck.

Our role: Editor and AI feature engineering

Cleverseed ships AI features on a weekly cadence, most of them written by the in-house team against the extension API. Inline diffs turned out to matter more than the model quality: writers accept roughly two thirds of suggestions and report trusting the tool because they see exactly what changes before it changes.

The company is now selling into agency teams, where the collaboration and review features built on the same schema are driving the deals. Our involvement has narrowed to architectural review as new node types are added.

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