Arcana serves institutional investors with analytics for portfolio risk decomposition and alpha identification. The stack—React, Python, SQL, ClickHouse, Redshift, Kinesis, and Bloomberg/FactSet connectors—reveals a data-forward architecture designed for real-time analytics at scale. Heavy engineering and data hiring, paired with active projects in multi-step agent pipelines and inference optimization, signals a shift toward AI-assisted portfolio analysis. Security and infrastructure maturity (hybrid cloud architecture, proactive security initiatives) track with the institutional investor audience and regulatory constraints of the space.
Notable leadership hires: Security Director, Director of Engineering, Sales Director
Arcana builds portfolio intelligence software for hedge funds and asset managers. The product surfaces portfolio risk metrics, decomposes single-stock and book performance, maps crowding dynamics, and isolates differentiation—all built on proprietary datasets covering ownership, factor risk, and crowding. The company operates at the intersection of institutional finance and data infrastructure, integrating feeds from Bloomberg and FactSet while maintaining its own crowding and factor models. Founded in 2022, Arcana is based in New York and employs 51–200 people across engineering, data, product, and sales functions across the US, UK, and India.
Frontend: React, HTML, CSS, JavaScript. Backend: Python, SQL, PostgreSQL, Redis. Analytics & data: ClickHouse, Redshift, PySpark, Airflow, Kinesis, Cassandra, HBase, Hadoop. Data sources: Bloomberg, FactSet. Infrastructure: AWS (EMR, Lambda, Glue, IAM, CloudWatch).
Portfolio intelligence tools, risk factor modeling, multi-step agent pipelines for inference, data aggregation, customer dashboards, and a talent engine. Active priorities include inference latency reduction, data operations efficiency, and client onboarding streamlining.
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