See your deck the way a VC will — before you send it.
Your raise is a journey with five stops. KRTR runs the same evidence engine investors use at every one of them.
Upload
Drop in the deck you'd send a VC. That's the whole onramp.
No forms, no setup. The deck you already have is the input — KRTR reads it the way a partner would, page by page.
Pre-diligence
An evidence-backed read: score, gaps, and open concerns — sourced, not guessed.
Dozens of typed agent passes over a living claim ledger produce your score, your gaps, and the open concerns — every one sourced and checked against live evidence, with an AI reviewer correcting whatever the evidence contradicts.
Fix the gaps
Work the same list a partner would push you on, before the raise instead of during it.
The gaps arrive as a concrete worklist: what to strengthen, what to substantiate, what to cut. Rerun when you've fixed them and watch the read change.
Match
Get in front of investors whose thesis actually fits your company.
Your profile is matched against investors whose calibrated thesis already wants companies like yours — so outreach starts warm instead of cold.
Close
Walk into every meeting knowing what they'll ask — and close faster.
Before each meeting, KRTR briefs you on the investor: their focus, their concerns, their style. You walk in knowing the questions.
You get one shot
A partner skims your deck in minutes. A fixable gap reads as a red flag, and there's no second first impression.
Silence, not feedback
Passes come with no reasons. You can't fix what nobody will name for you.
The polish arms race
Every deck is AI-polished now. Looking good stopped being a differentiator; holding up under scrutiny is the bar.
Months on wrong-fit investors
Most outreach dies on thesis mismatch that was knowable before you ever hit send.
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.
Start at stop one.
Upload your deck and see the read investors will see — while you can still change it.