i3 Data Confidence
We provide provide software that enables the confidence and integrity required for data communities based on I3 Software. Support for transparency, incentives, and data policy are built into the software's DNA.
i3 Data Management
Our I3 software to meet the needs of commercial and government data management network that uses data to interact across divisions, with partners, and with customers. The system supports real time data flows between applications and IoT devices, Features that provide for privacy,
Ecosystem Enhancement
We support IT departments, service providers, accelerators, application developers, and device manufacturers wishing to expand their data community. Transparency and integrity are needed to expand data use and increase data insights.

Our Mission

We Support Ecosystem Data Driven Innovation

Data Driven Insights

Innovation requires data, lots of data from lots of sources, and by creating a network of real-time data sources insights are accelerated

Economic Advantage

Innovation can be expensive but by making it easier for applications to find needed IoT data and by leveraging IoT device data IoT network economics are maximized,

Time Efficiency

Innovation takes time, by providing data when and where it is needed, concepts can be rapidly evaluated and operationalized

Use Cases

Recent Projects

Smart Parking
Smart Parking

Government Services

Community Security
Community Security

Shopping District

Healthy Environment
Healthy Environment

Community Healthcare

Video Analytics
Video Analytics

Service Demand Planning

The Latest News

The Coming IT Revolution

Gartner recently published their report “Top Strategic Technology Trends for 2022.”  End-of-year summaries and next year’s forecasts that fill inboxes this time of year are often discounted.  But this report was significant in that the identified trends suggest a significant shift in the tech culture. 

Among the trends identified by Gartner was a shift away from siloed applications where the infrastructure and processes needed to support applications are treated as independent needs toward a networked architecture where data, security, cloud, and privacy needs are managed cohesively across the entire enterprise.  The need for such a shift was echoed by multiple speakers at last month’s IoT World Conference.  The speakers discussed the need to reimagine existing data infrastructures in order to shift to horizontal platforms that better serve the enterprise.  Such a systemic restructuring requires enterprises to adopt a layered structure or a tech stack that compartmentalizes functionality and increases data visibility across the organization.  This leads to a more trusted approach to IT by increasing access to data and tools.  Ultimately, data utilization and collaboration are improved and the organization increases its return on investment.

Another highlighted trend is based on a movement toward a more dynamic applications environment.  The last few years have shown that nimble organizations are better able to adapt to changing business conditions.  Organizational agility can only be achieved if the IT organization is able to deliver in the face of evolving requirements if its toolkit includes composable applications, automation tools, business intelligence systems, and configurable artificial intelligence.  As IT evolves away from the idea of an all-encompassing application that limits adaptability, they are (1) adopting new systems that treat applications as a series of functional modules that can be restructured as needs change, (2) managing data as dynamic data flows that provide the freedom to rebalance data distribution systems as necessary, and (3) deploying rule-driven systems that allow insight advancement based on derived insights. 

Trending data also demonstrate that organizations are moving to embrace technologies that serve to adapt to the desired user experiences.  This trend represents a shift away from systems that might improve operational efficiencies if it comes at the cost of the human experience.  The days of deploying technologies that require organizational changes or significant employee retraining exercises are coming to a close as organizations embrace systems that enhance desired customer and employee experiences.  Technologies are emerging that support the needs of a distributed organizational structure.  Tools that emphasize customer (and employee) experiences are becoming expectations rather than desires.  And active intelligence systems that are able to process data and directly impact operational processes are supplanting systems that first capture data, mining the data for insights, and then recommend management action. 

The trends identified in the report go well beyond references to technology that an organization can purchase and deploy in an effort to achieve incremental process improvement.  They represent a new IT philosophy about how data systems are architected, operationalized, and perceived by the organization as a whole. 

IT function is continuing to evolve away from its roots as a service function to become an important component of any organization’s strategic mission.  Recent events have accelerated this migration in that the strategic objectives of any organization are either enhanced or limited based on the capabilities of the IT organization.  The trends identified by Gartner signify an acceleration of this movement.  Once these technologies are more fully deployed, the IT function further shifts from the role of being a key strategic advisor to the organization to being a much more active member of the management team.   IT is effectively shifting from being a strategic enabler (or inhibitor) of the organization to becoming a primary actor on the stage of future business.

Data Communities

Dictionary.com defines a community as a social, religious, occupational, or other group sharing common characteristics or interests and perceiving itself as distinct in some respect from the larger society in which it exists. Communities are often associated with physical locations such as neighborhoods, cities, or states. However, societal structures can also create the common interest that binds the members of the community. For example, college alumni associations, political parties, or religious affiliations can also serve to define a community that transcends geographical borders. For that matter, a company’s network of suppliers and their network of partners/integrators serve as two distinct communities that serve different purposes within each community bound by a common interest. The operational rules that define the community can be quite loose (e.g. Red Sox Fans) or they can be quite stringent and tightly managed (e.g SAG-AFTRA). However, seldom is the word “Community” utilized to refer to a network of data producers and data consumers even though the data usage does create communities of interest-based on the nature of the data.

Data communities are specialized communities made up of organizations that have data and organizations that want data tied together based on an intent-driven use of the data. A data community can exist within an organization, for example, there can be teams of data producers and data consumers that want to simplify the way they locate each other, exchange data, and utilize the data to increase data effectiveness within the organization. Data communities can be formed by peer organizations that both produce and consume data in different areas so those insights can be drawn by comparing or aggregating data to uncover a macro-level view of the data. Data communities can also be created that link suppliers and subcontractors of a larger company or the distribution and reseller chains that carry products to market. Data communities can even be formed based on a data marketplace where buyers and sellers come together to utilize data that can answer ad hoc or sustainable data needs.

For these data communities to thrive, there must be a sustained level of trust between the parties. Trust is not something that can be mandated by a higher authority and it is not something that can be purchased. Yes, management may be able to dictate that parties exchange data, or incentives can be attached to encourage the exchange of data but these measures are never sustainable. Communities are not just bound together by the exchange of data but by the trust that binds the participants together. Trust must be earned. One of the best methods to create an environment of trust is through transparency and choice. Transparency requires that both parties understand the motivations of the other party. For example, in a data community, the party receiving the data must understand the data they are being given; and the party transmitting the data must understand how the data will be utilized by the other party. The parties also need to be cognizant of the fact that any exchange of data can be terminated by either party if that party feels let down by the other party. Such disappointments may be based on data that is of lesser quality than expected, if one party is perceived as being less than forthcoming in describing the use case, or a party fails to accurately disclose the level of protection the receiving party provides the data.

In business school, students are taught that to maximize the value of a relationship between two members of a community, the parties must be candid, honest, and willing to share relevant information. The same is true in a data community – benefits are maximized when data is shared freely between partners. Unfortunately, not all partnerships live up to these expectations. As a result, there is often a reluctance to share data between partners because fear of failure often outweighs the desire to maximize benefits. What is needed is a way to clearly document expectations while providing an easy way to rescind established agreements when the terms and conditions are not being adequately met. These are core concepts that drove much of the work of the I3 Consortium and led to the formation of I3 Systems.


What people are saying

"i3 shows how to leverage data within the city so it is used and reused across the city in order to forward the entire mission of the City"

Joyce Edson
Joyce Edson Deputy CIO, City of Los Angeles

"i3 will create a much more sustainable approach towards data by making it easier to incorporate technologies needed to make communities smarter. "

Dr Bhaskar Krishnamachari
Dr Bhaskar Krishnamachari Faculty and Research, University of Southern California

"i3 is like credit card processing companies in that credit card companies provide the connection so money can flow - we need that for data"

Dhaval Kapadia
Dhaval Kapadia Founder, Startup Steroid