Data and workflow platform for residential real estate professionals
Perchwell operates a data platform purpose-built for residential real estate, with a tech stack shaped around Python, SQL, Airflow, Dagster, dbt, and Kafka—the typical infrastructure of a data-heavy business. The company is engineering-focused (6 of 11 active roles) with meaningful data investment (3 roles), but hiring has decelerated sharply (only 3 new roles in the last 30 days). Their project list reveals a company scaling data infrastructure to onboard MLSs faster while rebuilding frontend architecture—a pattern suggesting they're moving from early-stage custom work toward platform standardization.
Perchwell is a data and workflow platform for residential real estate agents, brokerages, and MLSs (Multiple Listing Services). Founded in 2015 and based in New York, the company serves the real estate industry with tools for data management, analytics, and workflow automation. The platform ingests property listings and market data across multiple MLS networks, then surfaces insights and workflow automation to help agents and brokerages close deals faster. Perchwell operates as a private company with backing from institutional investors and partnerships with leading MLSs.
Perchwell's core stack includes Python, SQL, Kotlin, Apache Airflow, Dagster, dbt, Kafka, and Kubernetes. They use AWS and GCP for cloud infrastructure, Figma for design, and HubSpot for CRM—reflecting a data-first platform with mobile (Android/Jetpack) and web surfaces.
Primary projects include building a data lake and warehouse for MLS clients, evolving data pipelines to ingest property listings and market insights faster, and rebuilding frontend architecture and state management. They're also scaling data infrastructure to handle rapid MLS onboarding—a key pain point.
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