In this presentation, SLACi provides a conceptual view of property operation, its data, sources of property information and the value of adopting a digital data strategy today.
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A lot of excitement surrounds the future of AI but most AI technology requires data to perform.

Public market data is necessary for PropTech on the business side of operations. However, public records offer limited information required to Service assets on the backend. Moreover, unreliable data usually results in costly errors and delays.

The most important information to technology in real estate is the property’s deep data. These details are usually stored in analog files with limited access.
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Real estate ecosystems don’t enjoy the continuity of a secure corporate network.

Unified access and exchange of data is challenged by the independence of service providers.

For example, build sectors along the top can produce digital data but most physical properties lack the infrastructure to receive digital deliverables and utilize data in operations.
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A typical commercial property has two basic ecosystems. Operations on the front end of business focus on markets, tenants and revenue.

Backend operations involving administrative maintenance, upkeep and tenant improvements tend to be a net expense. It’s also the least efficient part of property operation.
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PropTech on the business side of property management uses a combination of public and private information with limited use of deep data in proprietary platforms.

Vendor integration can increase expense and may be limited or include “end features” that add a technology process without autonomy.
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The digitization of physical property offers business and build service providers with a single source of reliable up-to-date data.

Property information assembled during construction, provides the foundational data, service providers need to market and maintain assets in operations.

SLACi builds infrastructure to capture, exchange and integrate this deep data into the digitization of property operations.
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Deep data emerges naturally in build. And it continually expands through daily operations, property upkeep and routine maintenance.

Centralized storage allow owners to capture data in real time from build and tenant improvements to operations documenting upgrades and service events.

User technologies will utilize this data to improve performance and dynamically initiate workflow autonomy between project stakeholders
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Property operates dynamically on a foundation of independent stakeholders constantly moving from one property and business task to the next.

SLACi pioneered a universal and reusable security solution that dynamically align service provider access to asset data as-required through shared project and workflow objectives.

AI Managed security features provide seamless data exchange between the property data, management and service provider technologies that digitally transform property operations.
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Data creates value by transforming manual workflows through augmented autonomy. SLAci publishes a number of white papers that explore how autonomy will creep into property operation.

In addition, it’s important property owners understand the digitization of property operation is deep tech that requires many user solutions that will emerge over time.

The process starts with deep data and infrastructure for secure access. Real estate ecosystem technologies will use this data to digitize property operations.
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The CaPSCi 200 program, kickstarts the AI data strategy for a limited number of physical properties. This is an early opportunity to leverage the internal and external value of deep data.

SLACi will assemble and prepare the assets basic AI dataset, including analog and digital data required to begin initiating workflow autonomy.

Program technology and benefits are tied to the physical property. These features survive changes in ownership to improve asset valuations.
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The CaPSCi 200 program, kick starts the AI data strategy for a limited number of physical properties. This is an early opportunity to leverage the internal and external value of deep data.

SLACi will assemble and prepare the assets basic AI dataset, including analog and digital data required to begin initiating workflow autonomy.

Program technology and benefits are tied to the physical property. These features survive changes in ownership to improve asset valuations.