WebCatalog

Alt-X

Alt-X

Alt-X 以資料與 AI 處理未結構化交易文件,標準化關鍵 KPI(如 ARR、NOI、IRR、cap rate),自動產生投資評估報告與儀表板,支援私募與不動產盡職調查。

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Private markets are still opaque, manual, and locked inside Excel. Every year, trillions of dollars in venture, real-estate, and private-equity capital are deployed through diligence processes that haven’t changed in decades. Analysts spend hours parsing PDFs and spreadsheets just to understand what a company or property is worth.

Alt-X is building the data and AI infrastructure layer for alternative assets — a system that ingests unstructured deal materials, normalizes the data, and generates institutional-grade analysis in seconds. Whether it’s a private-company dataroom or a real-estate offering memorandum, Alt-X extracts key KPIs like ARR, growth, NOI, IRR, and cap rate, then produces investor-ready dashboards and reports automatically.

Our platform reduces deal evaluation timelines by up to 73%, saves 30–50 analyst hours per deal, and enables teams to screen 4× more opportunities with the same headcount. By automating KPI extraction, benchmarking, and underwriting, Alt-X transforms diligence from a manual bottleneck into a scalable process.

This hasn’t been done at scale because private-market data is fragmented across formats and asset classes. Alt-X’s parsing engine unifies this chaos into a structured schema — the backbone for cross-asset underwriting, KPI dashboards, and automated risk scoring.

Our first wedge is real estate and private equity, where underwriting is slowest and most manual. We’re already piloting with family offices and private funds managing over $200 million in assets, paying $1K–$5K per month to automate deal screening and valuation.

The opportunity is massive: over $1.4 trillion in new private-equity and real-estate deals are underwritten globally each year, with $25–30 billion spent on diligence and analytics. Yet over 90% of this still happens manually. Alt-X’s mission is to become the operating system for private-market investing — the Bloomberg Terminal of the AI era.

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