Siepe operates a cloud data platform purpose-built for institutional asset management, running on AWS and Azure with a tech stack centered on C# and SQL Server. The company is actively modernizing away from Angular toward .NET and addressing core pain points around legacy reporting systems and performance at scale — investments that align with their engineering-heavy hiring (six roles open) and accelerating hiring velocity. Their project mix (structured finance compliance models, next-generation reporting UI, data pipelines, custom dashboards) reflects the reality of serving asset managers with fragmented data sources and evolving regulatory requirements.
Siepe provides managed cloud services and data analytics for asset managers, with a focus on portfolio management, risk management, and regulatory compliance. The platform ingests disparate data sources and surfaces portfolio transparency, operational risk mitigation, and process visualization through custom reporting and dashboards. Founded in 2012 by industry practitioners, the company operates at 51–200 employees and is headquartered in Dallas. Siepe's architecture spans cloud infrastructure (AWS/Azure), data warehousing (SQL Server), and modern frontend frameworks, with active development across structured finance compliance tooling, reporting interfaces, and internal data pipeline modernization.
Siepe runs on AWS and Azure, with C#, SQL Server, and TypeScript as core languages. The stack includes Terraform for infrastructure, Angular for UI (now being replaced), NgRx for state management, and Highcharts for visualization. SAML 2.0 and Active Directory handle identity.
Current projects include structured finance and CLO compliance models, next-generation reporting and analytics UI, advanced data exploration tools, custom client dashboards, and modernization of legacy reporting systems and .NET components.
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Siepe'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.