AI-first platform combining CPQ and commission management for revenue operations
Everstage operates a revenue operations platform that merges quote-to-cash and incentive compensation into a single system. The tech stack—SAP, Oracle, Salesforce, dbt, Apache Airflow, Looker, Tableau—reflects a B2B software company built to integrate deeply with enterprise finance and sales systems. Active projects center on customer onboarding (compensation plan implementation, instance configuration) and product experience (chat, interactive tours), while pain points cluster around pipeline generation and compliance/audit readiness, signaling that sales execution and regulatory governance are current operational constraints.
Everstage builds an AI-first platform for RevOps, Finance, and Sales teams that unites Configure-Price-Quote (CPQ) capabilities with commission and incentive compensation management. The product targets mid-market to enterprise companies seeking to automate commission payouts, align sales incentives with revenue quality, and ensure pricing decisions map to profitability goals. The company operates with 201–500 employees based in New York, founded in 2020. The hiring profile—concentrated in engineering and product with emerging finance and sales roles—reflects scaling of both the platform and go-to-market execution.
Everstage uses SAP, Oracle, Salesforce, dbt, Apache Airflow, Looker, and Tableau as core infrastructure, alongside HubSpot, Power BI, Google Analytics, and analytics tools like Ahrefs and Semrush for demand generation and performance measurement.
Everstage is an AI-first Revenue Transformation platform that combines CPQ and commission/incentive compensation management. It automates sales commission payouts, aligns incentives with strategic revenue goals, and ensures quote accuracy and profitability for RevOps, Finance, and Sales teams.
Everstage's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.