Infoblox has launched Infoblox IQ, an agentic artificial intelligence operations layer designed to help networking and security teams investigate incidents, prioritise alerts and execute approved actions across hybrid enterprise environments.The Santa Clara-based company is positioning the product as a bridge between enterprise infrastructure data and AI-driven operations, at a time when security operations centres and network teams are under pressure from alert volumes, fragmented tools and rising expectations for faster response. Infoblox IQ combines an AI assistant, automated agentic actions and Model Context Protocol integration, allowing teams to interrogate operational data through natural language and move from diagnosis to remediation without switching between multiple consoles.
The launch covers two initial product areas: Infoblox IQ for Threat Defense and Infoblox IQ for DDI. The first targets DNS security investigations, while the second focuses on DNS, DHCP and IP address management operations across Infoblox Universal DDI and NIOS environments. Infoblox IQ for Threat Defense is expected to be generally available by the end of June, while Infoblox IQ for DDI, the IQ assistant and the MCP server integration are available to early-access customers ahead of broader availability planned for autumn 2026.
The product continuously analyses DNS queries, DHCP leases, IP address assignments, device activity and security events flowing through the Infoblox platform. That data is used to identify issues, correlate events, recommend action and support configuration changes with an audit trail. Infoblox says one customer deployment reduced more than 504,000 operational events to 24 prioritised actions through agentic triage, while investigations that previously took 45 to 90 minutes of manual work were surfaced with immediate context.
Mukesh Gupta, chief product officer at Infoblox, said the company’s existing data gives it a clear view of enterprise network activity. He said organisations moving from AI pilots to operational deployments need infrastructure data that is trusted and current, adding that generic AI tools lack the visibility required for reliable autonomous action across DNS, DHCP and IPAM environments.
Scott Harrell, president and chief executive of Infoblox, described DDI as a long-standing foundation of enterprise networks and said the rise of AI makes that layer more important. He said Infoblox IQ turns infrastructure data from a system of record into a system of action, enabling organisations to respond more effectively and make better use of AI-driven operations.
The announcement reflects a wider shift in enterprise technology as vendors race to embed agentic AI into IT operations, cybersecurity, cloud management and workflow automation. Agentic systems differ from conventional analytics tools because they can reason across context, select actions and interact with external systems, although most enterprise deployments still require guardrails, policy controls and human approval for high-impact changes.
For security teams, Infoblox IQ is designed to reduce alert fatigue by linking threats, assets, users, devices and network activity into a single investigation path. The system collects evidence, analyses DNS activity and presents analysts with confirmed threats, affected users and recommended remediation steps. This approach is aimed at helping security operations centres focus on high-priority risks rather than repetitive alert review.
For network teams, the product monitors performance, configuration and capacity issues before they disrupt users. It can collect operational data, deliver root-cause analysis within seconds and suggest guided remediation steps. Infoblox says the DDI version can automate much of the work a network operator would otherwise perform after a ticket is opened, while keeping a record of recommended and executed actions.
A key element of the launch is Infoblox’s Model Context Protocol server, which makes the company’s network, security and asset intelligence available to third-party AI assistants, agents and applications through a standard interface. MCP has gained traction as enterprises seek a more consistent way to connect AI systems to tools and data sources, reducing the need for custom integrations. The protocol also brings fresh governance challenges, including tool authorisation, access boundaries and control over what agents can execute.
Infoblox is seeking to use its position in core network services to differentiate itself from broader AI operations platforms. DNS, DHCP and IP address management systems sit close to the operational base of enterprise networks, providing a live view of devices, users, services and traffic direction. That visibility is increasingly important as companies try to ground AI recommendations in authoritative infrastructure records rather than incomplete logs or isolated application data.
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