Digitizing Property Assets!
White papers and guides for transitioning physical property to digital assets
AI Data in Real Estate
Asset owners are pioneers in the digitization of physical property. They’ll transform how real estate industries operate! SLACi white papers explore emerging demand for AI data, user tech and industry sources.
Digitization of Property
What does the ‘Digitization of Property’ mean for property owners? In this article we offer a practical guide to four distinct applications of digitizing the deep data of physical property assets.
PIM Directory Structures
Learn how to structure property information model (PIM) details to maximize utility, enhance security and reduce technology process. SLACi recommends a minimum set of file folders to organize your AI data.
AI Data Library Intro
Real estate spans eight industry sectors so what an AI data library may contain depends on use case and sector. A property data library begins with secure accessibility to the property information model (PIM).
Best Storage Options for Property Data
Every property has its own AI data library that should be stored in the cloud but what type of storage offers the greatest advantage to property owners, investors and service provider ecosystems.
Digital Data Benefits for NNN Owners
Five reasons why NNN property owners should adopt a digital data policy. This article discusses AI, data utility and taking ownership of property data as an investment.
Autonomy in Property Operations
Autonomy augmented operation is expected to improve property valuations up to 5%. In addition, if deep data were available today, markets for analytics would offer owners $6 Billion in annual revenue.
Autonomy in Property Management
The acquisition of property services remains by large a manual process. We highlight three areas of autonomy in property management that will recover value time for managers to do more with less.
Insurance Document Autonomy
Explore how technology can process insurance documents without human intervention. In this article, we discuss how AI data, user security and technology integrate user workflows between organizations exchanging documents.
AI Data in Real Estate
Asset owners are pioneers in the digitization of physical property. They’ll transform how real estate industries operate! SLACi white papers explore emerging demand for AI data, user tech and industry sources.
Digitization of Property
What does the ‘Digitization of Property’ mean for property owners? In this article we offer a practical guide to four distinct applications of digitizing the deep data of physical property assets.
PIM Directory Structures
Learn how to structure property information model (PIM) details to maximize utility, enhance security and reduce technology process. SLACi recommends a minimum set of file folders to organize your AI data.
AI Data Library Intro
Real estate spans eight industry sectors so what an AI data library may contain depends on use case and sector. A property data library begins with secure accessibility to the property information model (PIM).
Best Storage Options for Property Data
Every property has its own AI data library that should be stored in the cloud but what type of storage offers the greatest advantage to property owners, investors and service provider ecosystems.
Digital Data Benefits for NNN Owners
Five reasons why NNN property owners should adopt a digital data policy. This article discusses AI, data utility and taking ownership of property data as an investment.
Autonomy in Property Operations
Autonomy augmented operation is expected to improve property valuations up to 5%. In addition, if deep data were available today, markets for analytics would offer owners $6 Billion in annual revenue.
Autonomy in Property Management
The acquisition of property services remains by large a manual process. We highlight three areas of autonomy in property management that will recover value time for managers to do more with less.
Insurance Document Autonomy
Explore how technology can process insurance documents without human intervention. In this article, we discuss how AI data, user security and technology integrate user workflows between organizations exchanging documents.