Embedded integration platform for AI agents and B2B SaaS products
Paragon provides integration infrastructure for B2B software companies, with a focus on AI-native use cases like agent tool calling and RAG ingestion. The stack reveals a sophisticated, distributed architecture: Node.js + TypeScript + NestJS on the API side, Kafka for event streaming, PostgreSQL + Redis for state, and Kubernetes for orchestration—paired with security-first tooling (SAST, DAST, KMS). The hiring mix is balanced across engineering, product, marketing, ops, and sales, with accelerating velocity and mid-level seniority dominant, suggesting a shift from founder-driven execution toward repeatable go-to-market processes.
Paragon is a 11-50 person embedded integration platform founded in 2019 and headquartered in Los Angeles. The company enables B2B software vendors to embed 130+ pre-built connectors and fully-managed authentication into their products, reducing integration build time significantly. The platform targets both traditional SaaS and AI-forward use cases—agent tool orchestration, RAG data pipelines, and native product integrations. Current focus includes automated integration workflows for AI agents, a data ingestion platform for retrieval-augmented generation, and end-to-end go-to-market process improvements.
Paragon runs Node.js, TypeScript, NestJS, PostgreSQL, and Redis on the core platform; Kafka for streaming; Kubernetes for orchestration; and AWS, GCP, Azure for cloud infrastructure. Security tooling includes SAST, DAST, and AWS KMS.
Paragon provides 130+ pre-built connectors, fully-managed authentication, and embedded SDKs designed for native B2B SaaS and AI product integrations.
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Paragon'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.