Adaptive Private Market Intelligence

The Knowledge Infrastructure for Private Markets

General AI won’t give you an edge. Your proprietary intelligence will.

Trusted by investment firms across the market

Also running on Kruncher: a financial-centre regulator in the UAE, a $14.5B fintech fund, a mid-market PE buyer, a multi-family office in Singapore.

Everything you know, in one place

Your firm’s own private PitchBook, updated every time an email, a call or a document arrives.

Open any company and see what it told you next to what the market shows, with every value traceable to its source. Each figure is labelled: what the company said, what the market shows, what Kruncher estimated, what your team concluded. Nothing is blended.

The record remembers what your firm decided along the way, and why.

Internal meets external

Your notes, calls and documents sit on the same timeline as premium data and live market signals, attached to the same company. No more reconciling by hand.

Always current

The record updates as new information arrives and shows what changed. When sources disagree, the more authoritative one wins, with both visible. Facts, estimates and your team’s opinions stay labelled.

Seen through your lens

The same company looks different to different investors. Kruncher scores every opportunity against your thesis and sharpens its assessment with every decision you make.

Why AI alone is not enough

AI reasons on whatever it retrieves. Access to a model and connected files is not the same as a reliable investment intelligence system.

Investment memo · ACME

Executive Summary

ACME builds power-flexible data centers for

GPU-intensive AI workloads, positioning it to

benefit from rising compute demand, grid

constraints, and enterprise appetite for

cheaper, flexible capacity.

Early signals look promising: reported growth

of roughly 25%, a building pipeline of enterprise…

Reply…

A model on its own does not

Resolve contradictions
Identify missing data
Apply your investment thesis
Know which source wins
Understand your firm’s history

The answer can look right while the underlying company view is wrong.

The main risk is not an obviously bad answer. It is a fluent, plausible answer built on an unresolved information foundation.

Keep Claude. Point it at Kruncher. Through the MCP server, the model you already pay for reads the resolved record instead of guessing from files.

Five layers every investment team needs

Automation is only as good as the reasoning under it, and reasoning is only as good as the knowledge under that.
Most tools deliver the top layer. Kruncher builds all five.

Kruncher in action

Most firms start with one. Investment teams start with screening, with the CRM they already run kept current underneath. Portfolio teams start with monitoring. Secondaries teams start with a fund.

Working on day one, configured in weeks. Built from how 500+ private equity and venture professionals use the platform, then bent to how your firm already works.

Origination Diligence Portfolio Monitoring Secondaries & Valuation

Origination

Find and screen companies against your thesis, follow the funds that lead your deals, and reach out to companies with the context you’d normally spend a week gathering. Learn more

Sourcing agents that track your thesis Rapid screening built for IC Outreach and relationship capture A live watchlist: growing versus declining, with alerts

Diligence

Compare companies in minutes instead of days, stress-test the investment case, and produce documents your IC can trace back to the source, line by line. Learn more

Configurable diligence checklists with gap tracking Side-by-side company comparison Memos and IC decks in your format Team review, comments and voting

Portfolio Monitoring

Request updates from every holding, combine whatever comes back with what the market already shows, and export numbers and narrative in the format the meeting expects, from internal reviews to the LP report. Learn more

Live FMV, ARR, and signal alerts LP reports in your own template Competitor tracking and add-on targets Add-on targets ranked by fit, for buy-and-build theses One dashboard across your whole book

Secondaries & Valuation

Pricing a secondary means rebuilding a portfolio from reports that arrive late and in a different format from every manager. Kruncher reads from the systems you already use, resolves each fund and company to a single identity, and carries every figure through to the model you price on. Learn more

Reads from the systems you already use, so nothing is entered twice One consistent identity for every fund and company across sources A confidence level on every figure before it reaches your model Reporting patterns learned once per manager, so accuracy compounds Populated valuation models and cash flow projections you can price from

Why Kruncher is different

Kruncher is built to plug into the stack you already run, not to replace it. It does the one thing none of these tools do.

CRM stores companies.
Kruncher understands them.

Data providers give one report for everybody.
Kruncher gives you your report.

General AI answers questions.
Kruncher provides proactive intelligence.

Portfolio monitoring shows financial updates.
Kruncher adds qualitative view and benchmarking.

An internal build gets you a prototype.
Kruncher gets you month nine.

Build it yourself

Kruncher is your new private market infrastructure

A CRM with automation and your firm’s knowledge in one place, giving your team solid foundations to build any app or use case on top.

What the firms running on Kruncher say

Selected case studies from our customers. See more here

Undisclosed

Mid-market PE · $850M AUM · USA

The firm has a buy-and-build thesis in facilities services, but sourcing relied on static spreadsheets and quarterly competitive reports. Kruncher built a continuously updated map of the sector, identifying 140 targets and ranking them against the firm’s acquisition criteria. The firm has since closed two as bolt-ons.

The team now spends its time evaluating the targets that fit and monitoring competitive threats, rather than assembling the information behind them.

Case study coming soon