Mapped

About Mapped

Mapped provides an AI-powered data infrastructure platform that automates the discovery, extraction, and normalization of data from building systems, sensors, and vendor APIs. This technology enables property owners and facility operators to efficiently access and integrate real-time data, significantly reducing the time spent on asset discovery and enhancing operational efficiency.

```xml <problem> Integrating data from diverse building systems, sensors, and vendor APIs is complex and time-consuming, hindering efficient access to real-time operational data. The lack of a standardized data layer forces developers to spend excessive time on data discovery, extraction, and normalization instead of focusing on application development. </problem> <solution> Mapped offers an AI-powered data infrastructure platform that automates the discovery, extraction, and normalization of data from various sources within commercial and industrial spaces. The platform connects to building systems, sensors, and vendor cloud APIs, extracting data using their native protocols. Mapped then employs machine learning to automatically tag and map the raw data into industry-standard semantic data ontologies like BRICK, Haystack, and REC. This normalized data is used to build a knowledge graph accessible through a GraphQL API, webhooks, and destination connectors, enabling developers and facility operators to efficiently access and utilize real-time data. </solution> <features> - Intelligent edge software connects to diverse real-world data sources, including building systems, devices, and vendor cloud APIs. - Automated data discovery and extraction within four hours. - AI-driven tagging and mapping of raw data into industry-standard semantic data ontologies (BRICK, Haystack, REC). - Knowledge graph accessible via GraphQL API, webhooks, and destination connectors. - Support for 70+ cloud sensor integrations, 14 geospatial formats, and 12 on-prem protocols. - Open-source data model (brickschema.org). </features> <target_audience> Mapped primarily targets property owners, facility operators, and solution providers in retail, warehouses, hospitals, airports, stadiums, campuses, offices, mixed-use developments, and data centers. </target_audience> ```

What does Mapped do?

Mapped provides an AI-powered data infrastructure platform that automates the discovery, extraction, and normalization of data from building systems, sensors, and vendor APIs. This technology enables property owners and facility operators to efficiently access and integrate real-time data, significantly reducing the time spent on asset discovery and enhancing operational efficiency.

Where is Mapped located?

Mapped is based in El Segundo, United States.

When was Mapped founded?

Mapped was founded in 2019.

How much funding has Mapped raised?

Mapped has raised $35.0M.

Who founded Mapped?

Mapped was founded by Shaun Cooley.

  • Shaun Cooley - CEO
Location
El Segundo, United States
Founded
2019
Funding
$35.0M
Employees
40 employees
Investors
MetapropNTT DOCOMO Ventures
M

Mapped

Mapped provides an AI-powered data infrastructure platform that automates the discovery, extraction, and normalization of data from building systems, sensors, and vendor APIs. This technology enables property owners and facility operators to efficiently access and integrate real-time data, significantly reducing the time spent on asset discovery and enhancing operational efficiency.

El Segundo, United StatesFounded 2019401K+ followers10/10 TractionRelative Traction Score based on online presence metrics compared to companies in the same age group.
Updated 20 months ago

Funding

$35.0M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

AV
Funding rounds are not available yet.

Founders

Product

Problem

Integrating data from diverse building systems, sensors, and vendor APIs is complex and time-consuming, hindering efficient access to real-time operational data. The lack of a standardized data layer forces developers to spend excessive time on data discovery, extraction, and normalization instead of focusing on application development.

Solution

Mapped offers an AI-powered data infrastructure platform that automates the discovery, extraction, and normalization of data from various sources within commercial and industrial spaces. The platform connects to building systems, sensors, and vendor cloud APIs, extracting data using their native protocols. Mapped then employs machine learning to automatically tag and map the raw data into industry-standard semantic data ontologies like BRICK, Haystack, and REC. This normalized data is used to build a knowledge graph accessible through a GraphQL API, webhooks, and destination connectors, enabling developers and facility operators to efficiently access and utilize real-time data.

Target Audience

Mapped primarily targets property owners, facility operators, and solution providers in retail, warehouses, hospitals, airports, stadiums, campuses, offices, mixed-use developments, and data centers.

Features

  • Intelligent edge software connects to diverse real-world data sources, including building systems, devices, and vendor cloud APIs.
  • Automated data discovery and extraction within four hours.
  • AI-driven tagging and mapping of raw data into industry-standard semantic data ontologies (BRICK, Haystack, REC).
  • Knowledge graph accessible via GraphQL API, webhooks, and destination connectors.
  • Support for 70+ cloud sensor integrations, 14 geospatial formats, and 12 on-prem protocols.
  • Open-source data model (brickschema.org).
1
This profile is AI-generated and may contain inaccuracies.