AI on Your Terms: A New Model for Secure Public Safety Technology

IRVINE, CA – December 09, 2025 – The adoption of artificial intelligence in public safety presents a classic double-edged sword. On one side lies the immense potential to accelerate investigations, manage mountains of digital evidence, and enhance operational efficiency. On the other, the sharp risks of data breaches, regulatory non-compliance, and the erosion of public trust loom large. For law enforcement and government agencies, navigating this high-stakes environment has often meant a cautious, slow-moving approach to innovation. A recent move by enterprise AI firm Veritone, however, signals a pivotal shift in this dynamic, offering a model that promises the power of AI without demanding a forfeiture of control.

Veritone recently announced that its aiWARE™ platform, including its flagship Intelligent Digital Evidence Management System (iDEMS), can now be deployed on self-hosted private tenants within a public safety agency's own AWS or Azure cloud account. This development moves beyond the standard, one-size-fits-all software-as-a-service model, directly addressing the paramount need for data sovereignty and security in the public sector. Instead of sending sensitive data to a vendor's cloud, agencies can now run Veritone's powerful AI engines inside their own secure, managed digital infrastructure.

“Veritone’s commitment to open architecture and interoperability ensures our platform can meet customers where they are, not the other way around,” said Ryan Steelberg, CEO and President of Veritone, in the company's announcement. This philosophy is at the heart of the new deployment option, which acknowledges that for organizations handling sensitive criminal justice or national security information, where data lives and who controls it are non-negotiable.

The Architecture of Control

To understand the significance of this shift, one must look past the marketing and into the technical architecture. Standard multi-tenant cloud services, while secure, operate on shared infrastructure where data from multiple clients is logically separated. For many commercial applications, this is sufficient. For a police department managing evidence for an active criminal case, the perception of shared resources can be a significant legal and procedural hurdle.

Veritone's self-hosted model empowers agencies to leverage the robust isolation capabilities of cloud giants like AWS and Azure for themselves. By deploying aiWARE within an agency’s own Amazon Virtual Private Cloud (VPC) or Azure Virtual Network (VNet), the platform is ring-fenced within a private, isolated section of the cloud. The agency defines the network rules, manages the access controls using their existing identity protocols, and dictates the flow of all information. This effectively creates a private data center in the cloud, owned and operated by the agency, but with the scalability and power of a hyperscale provider.

Further enhancing this control is the platform's hybrid-capable design. The aiWARE architecture can operate in a “hub and spoke” model, where the data ingestion and AI processing components (aiWARE Edge) run locally within the agency’s own on-premise or private cloud environment. This ensures that raw, sensitive data—such as unredacted body camera footage or confidential informant interviews—never has to leave the agency’s direct control. Only the resulting metadata or anonymized intelligence might be managed by the aiWARE Core, which acts as the system's analytical brain. This nuanced approach provides a critical layer of security, keeping the most sensitive information behind the agency's firewall while still leveraging the cloud for advanced analytics.

Navigating the Compliance Maze

For public sector IT leaders, the most significant barrier to adopting new technology is often the labyrinth of regulatory compliance. From the FBI's Criminal Justice Information Services (CJIS) Security Policy to federal standards like FedRAMP, the rules governing data handling are strict and unforgiving. A failure to comply doesn't just risk a fine; it can compromise evidence, jeopardize cases, and undermine an agency's legal standing.

Veritone's self-hosted deployment is engineered to navigate this maze. The iDEMS application is built to be CJIS-compliant, but by placing it within an agency's own controlled AWS or Azure tenant, the agency maintains direct oversight of the environment's configuration to meet every specific CJIS requirement. This is a game-changer for compliance officers, who can now apply their own established security protocols and audit procedures to the AI platform, rather than relying solely on a vendor's third-party attestations.

This model is particularly relevant for agencies aiming for FedRAMP authorization, a critical security standard for federal government cloud services. By deploying on pre-authorized environments like AWS GovCloud or Azure Government and maintaining control over the specific instance, agencies can significantly streamline their path to compliance. The ability to dictate data residency—ensuring data is physically stored within a specific jurisdiction or country—also directly addresses data sovereignty laws like GDPR and various state-level privacy acts, making it a globally relevant solution.

A New Foundation for Trust and Transparency

While operational efficiency and compliance are critical internal drivers, the external challenge of public trust is arguably even more important. The use of AI in policing is under intense scrutiny from civil liberties groups and the public, with valid concerns about algorithmic bias, surveillance overreach, and a lack of accountability. Providing a technological solution that also helps rebuild community confidence is the ultimate goal.

By enabling local control, Veritone’s model shifts accountability to where it belongs: the agency serving the community. When an AI system is operated within the agency's own controlled environment, it becomes easier to establish clear lines of responsibility for how data is used and how decisions are made. This counters the narrative of an opaque, unaccountable algorithm operating from a distant corporate server. The platform's features, such as immutable audit trails that provide a digital chain of custody for every piece of evidence, offer the kind of granular transparency needed to withstand legal and public scrutiny.

This technological framework supports the dual mandate of modern law enforcement: to solve crimes effectively while simultaneously increasing transparency. When an agency can demonstrate definitive control over its data and the AI tools that process it, it is in a much stronger position to engage with its community about how that technology is being used ethically and responsibly. This shift represents a maturation of the enterprise AI market, moving from disruptive force to a collaborative enabler, especially for sectors where trust is the most valuable currency.