Clinical platform for mental health treatment with AI-driven workflows
Osmind operates a clinical technology platform for moderate-to-severe mental health treatment, built on TypeScript/React/PostgreSQL with AWS infrastructure. The company is actively adopting Gemini while tackling technical debt and reliability issues—typical of scaling clinical software. Current hiring across engineering, sales, and operations (with senior/staff-level emphasis) suggests investment in platform maturity and go-to-market, not growth-stage hiring.
Osmind is a San Francisco–based public benefit corporation combining psychiatry, neuroscience, and engineering to develop treatment platforms and evidence-generating tools for moderate-to-severe mental health conditions. The product layer spans patient-facing treatment delivery and backend workflows for billing, prior authorization, and provider credentialing. Recent project focus includes a brand-new platform launch, workflow redesign, and AI tool integration—alongside foundational work on sales infrastructure and playbooks.
Osmind's stack includes TypeScript and React for frontend, Node.js for backend, PostgreSQL for database, and AWS (via ECS) for hosting. Data pipelines run on dbt and Fivetran; analytics on Metabase. They're adopting Gemini for AI capabilities.
Active projects include a brand-new platform launch, AI tools integration (especially for billing and coaching), workflow redesign, sales playbook development, technical debt reduction, and credentialing process improvements.
Osmind is hiring across the United States, Brazil, and Colombia. Current open roles span engineering (4), sales (1), finance (1), and operations (1), with emphasis on senior and staff-level positions.
Osmind'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.