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Compa

This company provides an AI platform designed to assist enterprise compensation teams with pay decisions using proprietary market data. The platform features AI agents that analyze market trends for compensation analysts and scale expertise for HR and recruiting stakeholders. It integrates with existing HR infrastructure to ensure accurate, real-time compensation alignment with company strategy.

Traction 10/10
Newport Beach, United States · HQ
Founded 2020965K+ followers
  • Artificial Intelligence
  • Data & Analytics
  • Enterprise Software
  • HR Technology
  • Software Only
Updated 2 days ago

Funding

Raised to date

$24MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

+28
Funding rounds are not available yet.

Founders

1 founder

Josh Schwede

Strategy/GTM Executive

Product

Problem

Traditional compensation surveys often provide outdated data, failing to reflect the rapid changes in today's volatile markets. This lag in information can lead to inaccurate benchmarking and uncompetitive compensation strategies, hindering talent acquisition and retention.

Solution

Compa is a real-time compensation market data platform that automates data submissions directly from human capital management (HCM) and applicant tracking systems (ATS). By aggregating and analyzing data from multiple sources, Compa delivers timely and precise market intelligence to compensation professionals. The platform enables users to benchmark employee cash, grant-level stock compensation, and the latest offer data with ease. Compa prioritizes data privacy, ensuring no personally identifiable information (PII) is exposed while providing competitive analysis.

Target Audience

Compa's primary customers are compensation professionals and human resources teams in organizations navigating dynamic talent markets, particularly in the tech sector.

Features

  • Automated data submissions from HCM, ATS, and stock administration systems
  • Multi-source matching using job codes, titles, and descriptions for precise benchmarking
  • Real-time market data on employee cash, grant-level stock compensation, and offer trends
  • Stock risk analysis to compare unvested equity values to the market in real-time
  • Data science layer to detect outliers at scale
  • Privacy measures including data minimums, privacy blockers, and smart filters
This profile is AI-generated and may contain inaccuracies.