Vise serves financial advisors with a portfolio construction and management platform built on a modern data and ML stack (Snowflake, Databricks, Apache Airflow, Python). The pain-point list—regulatory filings, reconciliation explanations, compliance integration, trading workflow bottlenecks—reveals a company scaling compliance and operations infrastructure alongside product features. Hiring is accelerating across engineering and finance, suggesting both technical and operational depth gaps as they move from launch toward enterprise adoption.
Notable leadership hires: Engagement Lead
Vise is a technology-enabled portfolio manager helping financial advisors create and manage personalized investment portfolios at scale. Founded in 2016 and headquartered in New York, the company operates as a privately held firm with 51–200 employees across the United States. The platform serves registered investment advisors (RIAs) and wealth management firms building customized, direct-indexed portfolios rather than relying solely on mutual funds or ETFs. Vise handles portfolio optimization, trading execution, regulatory filing, and client-facing reporting. Current focus areas include AI-driven portfolio tools for advisors, compliance monitoring, firm onboarding automation, and scaling enterprise customer success.
Vise's backend runs Python, Node.js, and Go on AWS and GCP, with PostgreSQL and Snowflake for data, Databricks for ML, Apache Airflow for orchestration, and React on the frontend. Operational tools include Salesforce, Retool, Jira, ServiceNow, and Bloomberg integration.
Core projects include portfolio optimization pipelines, a trading system, AI-driven tools for RIAs, regulatory filing execution, compliance monitoring and training, client-facing web applications, and enterprise onboarding automation.
Vise'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.