AI-powered quote-to-cash platform for multi-motion go-to-market
DealHub builds an integrated revenue orchestration platform spanning CPQ, billing, and subscription management with native AI agents for sales acceleration. The tech stack is heavily Java/Spring-based on the backend (Redis, Kafka, RabbitMQ for streaming) with deep ERP/CRM integrations (Salesforce, NetSuite, Dynamics 365, QuickBooks). Support and implementation dominate the hiring mix relative to engineering, reflecting a services-heavy motion focused on post-sale customer activation—a pattern reinforced by active projects around onboarding, configuration, and CS playbooks, and by stated pain points around adoption, implementation delays, and scaling post-sales operations.
DealHub delivers a quote-to-revenue platform for enterprises managing complex GTM motions: SLG, PLG, self-service, and consumption-based models. The product integrates CPQ and proposal generation with subscription and usage-based billing into a single orchestration layer. The company sells primarily into mid-market and enterprise segments and operates across sales, customer success, and finance teams. With 201–500 employees headquartered in Austin and hiring across the US, Israel, India, and the Philippines, DealHub is scaling its post-sales organization and partnership strategy to support portfolio companies in the investment ecosystem.
Java, Spring WebFlux, RxJava, Redis, Kafka, RabbitMQ on the backend; integrates Salesforce, NetSuite, Dynamics 365, QuickBooks, SAP; data infrastructure via Snowflake, BigQuery, Redshift, ClickHouse.
Yes. Support roles comprise 7 of 21 active positions and represent the largest hiring cohort. The company is also hiring engineering (5), sales (5), and data roles.
Austin, Texas. The company was founded in 2014 and is privately held with 201–500 employees.
DealHub.io'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.