Risk intelligence platform for sanctions, compliance, and financial crime screening
Kharon operates a knowledge-graph-based risk intelligence platform built on proprietary sanctions and compliance data. The tech stack reveals a data-heavy architecture—Neo4j, Neptune, Kafka, Airflow, Snowflake, PySpark—paired with modern application layers (React, FastAPI, Spring Boot), indicating active investment in both backend data pipelines and frontend consumption. Current hiring accelerates across engineering and sales while projects focus on tier-1 bank outreach and automating legacy compliance workflows, suggesting Kharon is scaling both product capability and go-to-market in high-friction compliance domains.
Notable leadership hires: Implementation Director
Kharon provides risk intelligence and screening solutions for financial crime, sanctions, and supply chain compliance. The platform combines a decade of expert research into a knowledge graph covering sanctioned parties, trade-restricted entities, forced labor networks, and illicit financial connections. Kharon serves mid-market and enterprise organizations across banking, investment, and government contracting sectors. Core use cases include sanctions screening, export controls, due diligence workflows, and investigative research. The company operates from Los Angeles with 51–200 employees and is scaling engineering and sales capacity.
Kharon's core infrastructure includes Neo4j and Neptune for graph queries, Kafka and Airflow for data pipelines, Snowflake for analytics, and AWS/GCP/Azure for hosting. Frontend built on React and Vue; APIs in Python, Java, and FastAPI.
Active projects include expanding sanctions monitoring, automating legacy compliance workflows, scaling accounting infrastructure, tier-1 bank sales, and building reporting frameworks. Projects align with reducing operational friction in compliance and growing enterprise customer base.
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Kharon'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.