BlueCat expands AI tools for network operations

BlueCat has introduced new artificial intelligence tools for network operations, including a preview of its MCP Server and a wider rollout of LiveAssist.

Both additions sit within the company's Intelligent NetOps platform, which brings together network identity, policy and telemetry data for operational workflows. The goal is to help organisations move from using AI for analysis to using it to investigate issues, automate tasks and take action across network environments.

The new MCP Server is designed to connect BlueCat's network data and related functions to external AI agents and platforms. It gives those systems structured access to real-time and historical network information, allowing them to query and analyse conditions and carry out actions within development tools, chat interfaces and broader business workflows.

The MCP Server also includes pre-built tools to help network operations teams develop workflows and support large language model-driven processes. It is available in preview across BlueCat's portfolio, with wider availability planned for the second half of 2026.

LiveAssist, BlueCat's AI co-pilot, is also expanding across more of the portfolio. It is already generally available with the company's network observability products and is due to extend to DDI through the BlueCat Horizon software-as-a-service platform under a usage-based pricing model.

BlueCat describes LiveAssist as a virtual engineer that draws on its combined data layer, documentation and support material. Through a conversational interface, teams can investigate faults, identify root causes and take follow-up steps instead of relying on separate systems for monitoring, configuration and support.

The announcement comes as technology suppliers and enterprise buyers seek to show that AI investments can deliver operational gains in core infrastructure. BlueCat cited a 2025 IBM study that found only 25% of AI initiatives had delivered the expected return on investment in recent years, linking that shortfall to fragmented data and disconnected systems.

Scott Fulton, Chief Product & Technology Officer at BlueCat, said the company was trying to address those gaps by unifying information from different parts of the network while giving customers flexibility over deployment and model use.

"We unify multi-vendor network data and give customers control over how and where AI runs, whether that's multiple deployment models, AI agents, or LLMs," Fulton said. "Our Intelligent NetOps foundation lets them put AI into production and see real returns, without putting network reliability and performance at risk."

The focus on network data reflects a broader shift in enterprise AI spending towards systems tied to operations rather than generic assistants. In network management, suppliers are increasingly trying to combine observability, automation and security data so AI tools can do more than answer questions and instead trigger changes or remediation steps.

BlueCat's approach centres on what it calls a unified data foundation, combining identity, policy, configuration and telemetry records. The company argues that this gives AI systems enough context to distinguish between anomalies, root causes and appropriate actions in environments that may include multiple vendors, hybrid infrastructure and cloud services.

That matters in network operations because fragmented data can limit how far automation can go. An AI model may be able to identify an unusual event, but without access to configuration rules, IP address management or historical telemetry, it may not be able to determine what caused the problem or whether any action would create additional risk.

BlueCat also used the announcement to underline the importance of deployment control. Customers can choose how and where AI operates, including different deployment models and the use of different agents or large language models, a point likely to resonate with organisations balancing automation with security and compliance concerns.

A customer partner also backed the broader strategy. Techary, a UK-based technology services partner, said BlueCat's architecture and pricing model reduced friction for customers and supported more accurate AI-driven operations.

"In complex environments, resilience and clarity aren't optional. BlueCat delivers both," said Mark Taylor, Enterprise Team Lead (Finance) at Techary. "Its flexible architecture and transparent pricing remove friction, and its unified data layer is what allows AI-driven systems to operate with real precision instead of guesswork."