Datarails Comparables

Find the most relevant public market comparables for Datarails, including EV/Revenue and EV/EBITDA multiples to help you make informed investment decisions.

Company Overview

Datarails is an AI-powered financial planning and analysis (FP&A) platform that automates data consolidation, reporting, and planning, enabling finance teams to continue using their Excel spreadsheets and financial models. It offers features like budgeting, forecasting, scenario modeling, data visualization, and an AI-powered chatbot for quick financial insights. The platform integrates with various ERP and CRM systems.

Business Model

Subscription-based software as a service (SaaS)

Target Customers

Small to medium-sized businesses (SMBs), mid-market companies, and enterprises; primarily finance teams who heavily utilize Microsoft Excel for financial planning and analysis.

Specific Focus

AI-powered FP&A solutions for Excel users, particularly small to mid-sized businesses (SMBs) and mid-market companies.

Location

New York, New York

CEO

Didi Gurfinkel

Industry

Software & services

Sub Sector

Financial Planning & Analysis (FP&A) Software

3yr Revenue Growth

1,372%

Public Market Comparables

Below are the key valuation metrics for companies similar to Datarails in the Financial Technology (FinTech) sector. These metrics can help you understand how the market values companies with similar business models and growth profiles.

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As a leading player in the Software & services industry within the Financial Technology (FinTech) sector, Datarails operates in the specialized Financial Planning & Analysis (FP&A) Software sub-sector. Understanding how Datarails compares to its public market comps is essential for accurate valuation and strategic decision-making.

Our comprehensive analysis includes detailed comparables (compsets) featuring similar companies in the Financial Planning & Analysis (FP&A) Software space, with complete financial metrics, growth trajectories, and competitive positioning insights that go beyond the surface-level data shown above.

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