Orb operates a revenue design platform built on a real-time data stack (Kafka, Spark Streaming, Apache Druid, ClickHouse) that unifies pricing, billing, and revenue intelligence for AI and SaaS companies. The tech foundation signals serious investment in handling high-volume, low-latency event streams—essential for usage-based pricing models. Hiring is currently engineering-heavy with acute focus on infrastructure resiliency and real-time ingestion scaling, indicating the company is managing rapid customer growth and the operational demands that come with being the revenue critical path for customers.
Notable leadership hires: Sales Director
Orb is a revenue design platform that helps AI and SaaS companies implement and operate usage-based pricing models. The platform unifies three core functions: pricing configuration (core pricing lifecycle primitives), billing execution, and revenue intelligence—allowing companies to evolve monetization strategies without re-architecting their stack. Built on raw usage events from customer deployments, the product ingests and processes high-volume data streams in real time. Operations are centered in San Francisco with a 51–200 person team; active hiring focuses on engineering for infrastructure and scaling, alongside sales and post-sales support for customer implementations.
Orb's stack is TypeScript and React on the frontend (with Tailwind CSS), Python on the backend, PostgreSQL for relational data, and Apache Druid and ClickHouse for real-time analytics. Event processing runs on Kafka and Spark Streaming; cloud infrastructure is AWS.
Current project priorities include infrastructure resiliency and recovery, scaling real-time ingestion and query systems, core pricing lifecycle primitives, product data model evolution, and improving the sales-to-implementation handoff for customers.
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