AI platform converting patient conversations into real-world evidence for life sciences
Mama health operates a patient-engagement and data platform targeting life sciences teams with chronic disease insights. The stack—Python, PostgreSQL, BigQuery, Snowflake, Redshift, Apache Airflow, dbt, Dagster, scikit-learn, PyTorch, TensorFlow—reveals a data-engineering-heavy operation focused on ingestion, transformation, and ML inference at scale. Active projects show dual momentum: deepening the patient app and analytics layer while ramping a US sales motion, a shift mirrored in hiring acceleration across sales and product roles.
Mama health is an AI-powered healthcare platform that captures structured insights from patient conversations about chronic disease experiences. The company operates a two-sided loop: patients share their healthcare journeys and receive personalized, evidence-based support through an AI chatbot; life sciences teams (pharma, medtech, payers) access real-time dashboards of unmet needs, care barriers, and emotional drivers in disease management. Based in Berlin with 11–50 employees, the company is scaling its data infrastructure (monitoring pipeline reliability, managing growth in data volume) while preparing major customer rollouts and expanding into the US market.
Python, PostgreSQL, MySQL, BigQuery, Snowflake, Redshift, Apache Airflow, dbt, Dagster, Prefect, pandas, scikit-learn, PyTorch, TensorFlow, AWS, GCP, Azure, TypeScript, React, FastAPI, and LiteLLM.
Building a patient journey analytics platform and data backbone for real-world evidence; launching a pharma sales motion; implementing pipeline monitoring and quality checks; expanding into the US market.
mama health'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.