Rowspace Launches with $50 Million to Unify Messy Financial Data Using AI

San Francisco-based fintech startup Rowspace has launched publicly with $50 million in combined seed and Series A funding, backed by Sequoia, Emergence Capital, and Stripe. Founded by former Notion CTO Michael Manapat and former Uber corporate development director Yibo Ling, the company uses AI to unify scattered financial data for private equity firms and institutional investors.

The Problem

Private equity firms manage financial data across dozens of disparate systems: portfolio company financials in spreadsheets, deal documents in shared drives, market data from Bloomberg terminals, fund administration data from third-party service providers, and correspondence in email. Assembling a coherent view of a portfolio's performance requires manually pulling data from these systems, reconciling discrepancies, and building reports — a process that can take days and is prone to errors. Rowspace automates this aggregation using AI that understands financial document structures and can extract, normalize, and reconcile data across formats.

How It Works

Rowspace connects to a firm's existing data sources — document repositories, accounting systems, portfolio management platforms, and email — and uses language models fine-tuned on financial data to automatically extract relevant numbers, dates, and relationships. The system then normalizes this data into a unified schema, flagging discrepancies and providing an auditable trail from each reported number back to its source document. Partners can query the system in natural language: "What was the EBITDA margin trend across our healthcare portfolio companies in Q4?" returns a chart with source citations.

Stripe's Involvement

Stripe's participation as an investor signals potential integration with Stripe's financial infrastructure for portfolio companies that use Stripe for payments processing. For private equity firms, having real-time visibility into a portfolio company's Stripe transaction data — rather than waiting for monthly financial statements — could provide earlier signals of performance changes and reduce the reporting lag that characterizes traditional private equity portfolio management.