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HEARTBOT AI Launches AnyInsight Edge, Ending the Trade-Off Between Private AI and Agentic Productivity

Money Compass by Money Compass
November 12, 2026
in PR Newswire
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HEARTBOT AI Launches AnyInsight Edge, Ending the Trade-Off Between Private AI and Agentic Productivity
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Private AI is no longer an island: a single control plane unifies policy across cloud and on-premises, extending a zero-trust generative AI firewall and AI governance to on-premises infrastructure and AI servers

TAIPEI, Nov. 12, 2026 /PRNewswire/ — HEARTBOT AI today announced AnyInsight Edge, extending its enterprise AI security and governance platform, AnyInsight, to on-premises environments and AI servers.

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AnyInsight Edge applies one control plane to private on-premises models and cloud AI. (Image: HEARTBOT AI)
AnyInsight Edge applies one control plane to private on-premises models and cloud AI. (Image: HEARTBOT AI)

Enterprises adopting AI have long been forced to choose between two paths. Private large language models (LLMs) keep data in-house but struggle to deliver the productivity of AI agents and automated workflows. Cloud AI offers the most capable models and agents, but data subject to residency or regulatory requirements cannot always be sent to external services, and governance becomes fragmented across providers.

AnyInsight Edge removes that trade-off. Through a single control plane, policy is managed centrally and enforced consistently across cloud and on-premises environments, so enterprises can use private on-premises models alongside leading cloud models to build AI agents and automated workflows. Every AI interaction, agent action and workflow execution is inspected in real time, access-controlled and fully logged, leaving no gaps in control.

Why Private AI Became an Island

AI is moving beyond chat toward AI agents and agentic workflows that execute multi-step tasks autonomously. The key to enterprise AI is no longer simply deploying a model, but whether AI can securely access enterprise data, connect to internal systems, run automated workflows, and maintain consistent governance and protection across every environment.

Many enterprises and institutions bound by data residency rules, regulation or customer contracts have already invested in AI servers and deployed private LLMs. Once live, however, these models often remain internal chatbots: cut off from core on-premises and cloud systems such as ERP, MES and CRM, they cannot support agents or automated workflows, and governance has to be built in-house. Even when teams wire up integrations themselves, new risks emerge. Agents read and move data across systems inside the corporate network as east-west traffic that never passes the network firewall. Agents that departments set up on their own and point directly at on-premises model endpoints become “shadow agents” invisible to IT, and data once protected by each system’s own access controls slips out of governance.

Cloud AI services, on the other hand, each come with robust security controls of their own. But when an enterprise uses several of them, policies and usage records are spread across platforms and hard to manage under a single standard, and some regulated or contract-bound data is not suited to external services. Without sanctioned AI tools in place, employees turn to public AI services on personal accounts, creating “shadow AI” that the organization cannot see or control.

Single Control Plane: Centralized Policy, Consistent Enforcement Across Cloud and On-Premises

AnyInsight Edge is delivered as a container with a hardware-agnostic design, deployable on-premises or integrated with an AI server’s operating system. Edge itself requires no GPU, leaving compute resources entirely for model inference. Policy and management can be initiated locally on Edge or synchronized with the cloud platform, while Edge acts as the policy enforcement point (PEP) in the on-premises AI traffic path, inspecting and enforcing in real time. The architecture can also extend to fully air-gapped environments, where Edge independently provides governance and AI firewalling for AI servers with no cloud connection.

  • Agents and automated workflows for private LLMs: Through Edge, on-premises models such as Gemma, TAIDE and Mistral gain access to AnyInsight’s 350-plus ready-to-use AI agents, automated workflows and more than 500 application connectors, with policy-based routing to over 20 leading cloud models when needed.
  • Every AI server becomes a governed AI server: Once an AI server runs AnyInsight Edge, it gains an AI gateway and a zero-trust generative AI firewall. Every request to and from the model, whether a conversation, a file transfer or an application integration, is inspected and logged by the policy engine. Access to on-premises models can be centrally controlled through Edge, so unapproved agents cannot call the models directly.
  • Core data stays in-house: Company databases, AI conversations, transferred data, access settings and audit logs can all remain on-premises. Data is tiered by recency, and long-term cold data can be centralized on-premises for stronger data protection and resilience.
  • Consistent enforcement across sites, with a single view: Offices, remote employees and multiple on-premises sites share consistent access controls and detection rules, with events and audit records consolidated in a single pane of glass.

Complementing Existing Network Firewalls, Without Decryption

Traditional network firewalls govern traffic and access at the network layer; the zero-trust generative AI firewall inspects the content of AI interactions. The two operate at different layers and complement each other.

Because AI traffic terminates at AnyInsight Edge, enterprises can understand the semantics of prompts without TLS decryption on the firewall and without upgrading existing equipment. The network firewall blocks unapproved AI services and steers AI traffic to AnyInsight, with network-layer and content-layer policies synchronized and events monitored centrally for defense in depth.

Agentic Security: From Inputs and Outputs to Every Agent Step

As AI agents begin to execute tasks autonomously, protection must extend beyond user inputs and model outputs to the information agents access, the tools and platforms they call, and the data they move between systems. Because an agent’s next step cannot be predicted in advance, control must be applied step by step at runtime; this is the core of agentic security. Traffic between agents and internal systems inside the corporate network never passes the network firewall, so it must be governed close to the source by Edge deployed on-premises.

AnyInsight applies context-aware semantic analysis to detect sensitive content such as personal, financial and health data and cloud credentials, and can alert on, block or mask it in real time. Before an agent calls any tool via the Model Context Protocol (MCP), policy is checked and access is authorized by role under the principle of least privilege; high-risk actions in agents and automated workflows require human approval. Every event is logged as exportable audit evidence.

Use Cases: Manufacturing, Finance, Government and Healthcare

  • Manufacturing and semiconductor supply chains: Process parameters, yield data and customer drawings never leave the plant, while on-premises models still compile production reports and anomaly analyses through agents and automated workflows, with a consistent security baseline across multiple sites.
  • Banking and insurance: Customer personal data is masked before it reaches the model, and every AI use and agent action leaves an auditable record, supporting regulatory and internal control requirements.
  • Government and healthcare: Official documents and medical records stay within the agency or hospital and are processed by on-premises models. The same platform provides AI interaction disclosure, human review and complete audit trails, in line with the direction of Taiwan’s AI Basic Act and the transparency and human oversight requirements of the EU AI Act.

“Twenty years ago, firewalls, intrusion prevention and VPNs converged into UTM, and that is when enterprise security finally caught up with the internet,” said Nathan Yen, CEO of HEARTBOT AI. “AI is at the same turning point. Models will keep changing and agents will keep multiplying, so enterprises need a control point that enforces policy where AI work actually happens. AnyInsight Edge turns every AI server into that control point.”

About HEARTBOT AI

HEARTBOT AI develops trustworthy, high-assurance enterprise AI solutions. Its flagship platform, AnyInsight, is a zero-trust enterprise AI security and governance platform with a built-in generative AI firewall, role-based access control (RBAC) and auditable activity logs. AnyInsight helps organizations protect sensitive data and enforce AI governance across platforms and networks. Enterprises can securely and rapidly connect their data and business applications, adopt AI agents and automated workflows to boost productivity and knowledge management, and keep complete records ready for compliance audits.

AnyInsight is certified to ISO/IEC 27001:2022 for information security management, and its AI governance and data protection mechanisms are designed on the principles of the EU AI Act and the General Data Protection Regulation (GDPR).

More information: AnyInsight | HEARTBOT AI

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