Cloud financial planning and healthcare analytics platform
Strata Decision Technology operates a cloud analytics platform for healthcare finance and budgeting, built on Python, PyTorch, and Snowflake with a heavy ML footprint (NumPy, Pandas, PyMC, spaCy). The active project list—AI agents, ML embedding, cost accounting, episode analytics—reveals a near-term pivot toward AI-driven insights; the tech stack (PyTorch, PyMC) and hiring velocity (accelerating, senior-weighted) confirm this is engineering-led, not a mature sales-automation play. Internal pain points around data reliability and scaling the data platform suggest they're solving infrastructure challenges alongside product innovation.
Strata Decision Technology is a public software company headquartered in Chicago, founded in 1996. The platform targets finance teams in healthcare systems, higher education, and financial institutions with cloud-native solutions for budgeting, financial planning, cost accounting, and performance analytics. The product surface includes StratJazz (a core budgeting and analytics suite), cost accounting and service-line margin reporting, and contract modeling for payor negotiations. Strata operates across 201–500 employees and is actively hiring engineers, data scientists, and finance professionals in the United States.
Python, PyTorch, NumPy, Pandas, Polars, PyMC, AWS (Lambda, SQS, SNS), Snowflake, Dagster, dbt, PostgreSQL, SQL Server, React, Tableau, Power BI, .NET, C#, Salesforce, and Oracle.
Active projects include StratJazz implementation, cost accounting and service-line margin analytics, AI agents and ML computation engines, payor contract modeling, and advancing AI/ML capabilities across the platform.
Strata Decision Technology'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.