
Mapped is an AI-powered independent data layer for commercial and industrial spaces, targeting property owners, facility operators, and solution providers. It automates the discovery, extraction, and normalization of real-time data from building systems, sensors, devices, and vendor APIs, abstracting integration complexities through machine learning and an open-source data model (brickschema.org). Their intelligent edge software connects to diverse data sources, maps data into industry-standard ontologies like BRICK, Haystack, and REC, and provides access via a knowledge graph with a GraphQL API, webhooks, and destination connectors. Customers across retail, warehouses, hospitals, airports, stadiums, campuses, and offices use Mapped to manage their data pipeline, enabling developers to focus on application development and outcomes. Mapped offers a unified API for all data, simplifying integrations and allowing applications to be deployed across any Mapped-enabled building.

Mapped is an AI-powered independent data layer for commercial and industrial spaces, targeting property owners, facility operators, and solution providers. It automates the discovery, extraction, and normalization of real-time data from building systems, sensors, devices, and vendor APIs, abstracting integration complexities through machine learning and an open-source data model (brickschema.org). Their intelligent edge software connects to diverse data sources, maps data into industry-standard ontologies like BRICK, Haystack, and REC, and provides access via a knowledge graph with a GraphQL API, webhooks, and destination connectors. Customers across retail, warehouses, hospitals, airports, stadiums, campuses, and offices use Mapped to manage their data pipeline, enabling developers to focus on application development and outcomes. Mapped offers a unified API for all data, simplifying integrations and allowing applications to be deployed across any Mapped-enabled building.
Elevator: AI-powered unified data layer that discovers, extracts, normalizes and serves building systems and sensor data via a standardized API
Customers / scale: Claims 1,000+ sites across 250M+ sq. ft. and 100M++ normalized data points processed
Integrations: 150+ integrations and support for industry ontologies (BRICK, Haystack, REC)
Founding / HQ: Founded July 2019; founder & CEO Shaun Cooley; headquartered in El Segundo, California
Multiple rounds with a Series A announced Jun 23, 2025; total funding reported in evidence: 12,000,000 USD
Data integration and normalization for commercial and industrial building systems and IoT.
2019
Smart buildings / PropTech / Building data infrastructure
“Mapped is backed by multiple venture and corporate investors including Greycroft, Singtel Innov8, MetaProp, Allegion / Allegion Ventures and ANIMO Ventures”
About Mapped Mapped is an AI-powered data platform for commercial and industrial spaces that helps property owners, facility operators, and solution providers to rapidly access real-time data from building systems, sensors, devices, and vendor APIs by automating the data discovery, extraction, and normalization process. Mapped uses machine learning to abstract the complexities of data integration to create an independent data layer with an open-source data model.
About The Role As a Senior Python Software Engineer (Data, AI, Graph), you'll build scalable backend systems that power seamless human-AI interactions at enterprise scale. You'll work with graph databases, machine learning pipelines, and real-time data processing to tackle a core challenge: how do we build the data infrastructure and algorithms that make complex AI feel effortless to human users for buildings?
We're looking for an engineer who shares our passion for data and thrives on solving complex algorithmic and system challenges. The ideal candidate has strong experience developing and deploying large-scale services in production, with expertise in Python, distributed systems, and either graph technologies or ML infrastructure.
What You'll Do
Qualifications Must-have Skills
Nice-to-have Skills