Venture decisions, built on evidence.
Every claim on KRTR is sourced, checked, and visible to both sides of the table. Built to keep pace with AI, not chase it. Pick your side.
See your deck the way a VC will — before you send it.
- The same evidence engine investors trust, pointed at you first
- Every gap a partner would flag, surfaced before the raise
- Matched to investors whose thesis actually fits
Screen every deck through your thesis, in minutes.
- Forward a deck, get audited pre-diligence back
- A score you can defend to partners — sourced, not guessed
- Screen → vault → portfolio, all agent-operable
From inbound to portfolio — one operating loop
Deals enter thin and arrive substantiated — then keep living: decision, deal lifecycle, portfolio. Every step is agent-operable; founders iterate and come back stronger.
New AI diligence tools launch every week.
Here's what they can't copy.
Reliability you can audit
A wrapper gives you a confident paragraph.
KRTR gives you a claim ledger — every statement sourced, checked against live evidence, and corrected by an AI reviewer when the evidence disagrees.
A memory that compounds
Prompt tools start from zero on every deck.
Every screen feeds a living network memory that sharpens the next read. That lead widens daily — and it can't be retrofitted.
Agent-native, not agent-washed
Others bolt a chatbot onto a dashboard.
Every KRTR operation is a typed, agent-callable verb behind an open protocol. Point Claude, Cursor, or your own fleet at the whole deal.
Built to outpace the curve
Legacy tools ship a feature a quarter.
Agent-first architecture means new capabilities land as verbs, not rebuilds — screening grew into deal vaults and portfolio in months, one system end to end.
Thinking of building in-house? Before your first sharp read, you'd be rebuilding the evidence gate, the claim ledger, the compounding memory, and the agent surface. KRTR is that build — already running, already learning.
