The application layer
for work context.
Every platform cycle produces an application layer the platform provider doesn't own. LLMs are no different. yarnnn is building that layer for work — an autonomous AI platform that connects to your tools, accumulates your context, and runs work-agents on schedule.
We're raising $500K pre-seed at $5M post-money.
The raise
$500K
Pre-seed round
$5M
Post-money valuation
$9–19
Per month pricing
$1.14B
SAM
Use of funds
Senior Tech Lead — accelerate context engine and agent architecture
GTM Lead — drive adoption in solo consultant wedge
Candidates identified from enterprise consulting network
Stage
Delaware C-Corp, pre-revenue
MVP live with all four integrations shipping
Solo founder — full stack built and shipped independently
What's live
Four integrations
Slack, Gmail, Notion, and Google Calendar — all connected and syncing. Cross-platform context accumulates automatically with every sync cycle.
Two operating modes
TP Chat for context-aware conversations. Headless mode for scheduled work-agents — weekly updates, project summaries, meeting prep — generated without prompting.
90+ ADRs
Architecture Decision Records documenting every design choice — from the unified content layer to five-mode agent intelligence. This is a purpose-built context engine, not an API wrapper.
Compounding moat
After 90 days of accumulated context, the system knows your preferences, your clients, and your style. Switching to a competitor means starting from zero. The moat deepens automatically with every cycle.
Investment thesis
Context is what makes autonomy meaningful — and cross-platform context accumulation is the application layer that no existing company is positioned to own.
Google didn't become Salesforce. Facebook didn't become Shopify. AWS didn't become Datadog. General-purpose platforms always look invincible — until the application layer emerges. LLM providers built code first (the easy case). Work context is the hard case: unstructured, personal, cross-platform, and domain-specific. Nobody is building that layer yet.
The comparable companies that validated this market — Notion ($11B), Glean ($7.2B), Granola ($250M), Mem.ai ($110M) — all proved demand for AI-powered context. yarnnn adds the autonomous output layer that none of them have.
Market
$4.35B
TAM — AI productivity tools, 31% CAGR
$1.14B
SAM — 5M solo consultants at $228/yr
$11.4M
Entry SOM — 50K users in 3 years
Entry wedge: solo consultants managing multiple clients with recurring work-agents across 3+ tools. Clearest pain, shortest sales cycle, highest willingness to pay. Expansion path: founders, executives, teams, then all knowledge workers.
Founder
Kevin Kim — Solo Founder & CEO
Korean-born, US-based. A decade of work spanning enterprise systems, cross-border operations, and context architecture — from deploying CRM for Japan Tobacco in post-military Myanmar to building GTM systems for cross-border sales teams.
Shipped the entire MVP solo: full-stack application (Next.js + FastAPI + Supabase), four platform integrations, unified agent architecture documented across 90+ Architecture Decision Records, and a working context accumulation engine — all before raising a dollar.
Let's talk.
If you're investing at pre-seed in AI infrastructure, work tools, or autonomous agents — I'd love to share the deck and walk through the architecture.
kvkthecreator@gmail.com