What challenges did BMC face before AI implementation?

Enterprises struggle with reactive IT service management and alert fatigue from multiple observability tools. BMC Helix needed to deliver intelligent, automated support that provides specific action plans rather than generic alerts. They aimed to create reasoning AI agents that understand observability data interrelations and past ticket resolutions.

What was the impact of the AI solution?

Customers using BMC Helix with Vertex AI reduced mean time to recovery (MTTR) by 25-35%, improving uptime for mission-critical IT environments. The platform enables proactive issue detection and resolution, freeing IT teams from reactive tasks to focus on business partnership. The deployment simplified model switching and accelerated AI innovation, giving BMC Helix a competitive edge.

Source

GCP

BMC Helix improves IT service reliability with autonomous AI agents on Vertex AI

Use case typeIT operationsUpdated Jun 13, 2026

BMC Helix provides IT service management solutions that use autonomous AI agents on Vertex AI to move beyond reliability towards innovative ServiceOps. They fine-tuned open-source Llama 3.1 8B models on Vertex AI using a Mixture of Experts architecture to help AI agents reason over observability data and provide actionable insights. The AI agents are deployed securely in customer clouds and integrated with applications like Slack and Teams for proactive IT operations.

Organization: BMC
Industry: Tech & Comms
Location: United States

Reported outcomes

−35%

timeTime & speed

Strategic outcomes

New product / capabilityDelivered autonomous AI service agentsCustomer experience & trustImproved service reliability and uptimeSpeed & agilityEnabled proactive issue resolutionCompetitive differentiationStrengthened competitive differentiation

Catalog median for time & speed deployments: −60% across 727 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 3

1AI Agents
2IT Operations
3ServiceOps

Enterprises struggle with reactive IT service management and alert fatigue from multiple observability tools.
BMC Helix needed to deliver intelligent, automated support that provides specific action plans rather than generic alerts.
They aimed to create reasoning AI agents that understand observability data interrelations and past ticket resolutions.

BMC Helix fine-tuned Llama models on Vertex AI with efficient Mixture of Experts architecture to analyze observability data holistically and reason about IT environments.
They integrated HelixGPT AI agents into collaboration tools like Teams and Slack to provide actionable plans and autonomous operations.
Customers can deploy HelixGPT models in their own Google Cloud environments for data privacy and control.

Technologies

Vertex AI Llama 3.1 8B Mixture of Experts architecture

Customers using BMC Helix with Vertex AI reduced mean time to recovery (MTTR) by 25-35%, improving uptime for mission-critical IT environments.
The platform enables proactive issue detection and resolution, freeing IT teams from reactive tasks to focus on business partnership.
The deployment simplified model switching and accelerated AI innovation, giving BMC Helix a competitive edge.

Architecture

Fine-tuned Llama 3.1 8B models on Vertex AI using Mixture of Experts architecture; integrated AI agents with Slack and Teams; deployed models securely on customer clouds; used Group Relative Policy Optimization for training planning agents.

Sources & evidence1

Groundedness: 5/5

Primary source

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Customer evidence