AI platform automating policy underwriting and quote generation
Federato builds an agentic AI platform for the insurance policy lifecycle, with engineering-heavy hiring (9 of 23 roles) focused on annotation, implementations, and delivery infrastructure. The stack—React, TypeScript, Node.js, Kafka, Python, PostgreSQL, Kubernetes, Kubeflow, dbt, Apache Airflow—signals a data-intensive, ML-first architecture designed to handle document processing and workflow automation at scale. Active pain points (underwriting cycle time, manual triage, legacy core system integration) map directly to their project focus on insurance document annotation and customer implementations.
Federato is an AI-native platform for the insurance industry, headquartered in San Francisco and founded in 2020. The product spans the full policy lifecycle—from quote generation through underwriting—using agentic AI to produce explained, strategically aligned policy quotes for underwriter review. The company operates at 51–200 employees with active hiring across the US, UK, and Australia. Current project work centers on customer implementations, annotation schema development, and delivery playbooks, while also building out early sales motion and top-of-funnel initiatives.
Federato uses React, TypeScript, and Node.js on the frontend; Python, Django, PostgreSQL, and Kafka for backend services; Kubernetes for orchestration; and Kubeflow, Apache Airflow, Dagster, and dbt for data and ML workflows. GCP serves as the cloud infrastructure.
Federato is hiring in the United States, United Kingdom, and Australia, with roles spanning engineering, sales, marketing, support, data, finance, product, and security.
Federato'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.