Future-proof enterprise AI stacks infrastructure that
deliver measurable outcome without collapsing under cost
misalignment or governance risk.
Accelerated
path to revenue
Overall business
expenditure reduction
Greater security
over corporate assets
Extensive review of an organization’s cybersecurity environment where AI is in use, including evaluation of SIEM, SOAR and XDR platforms where AI can be improved or augmented with AI agents.
Proactive compromise assessments, vulnerability and penetration testing, and tabletop exercises for compliance and preparation.
Establishes a readiness maturity model and detailed report of an organization’s cybersecurity portfolio and ability to leverage AI use cases throughout the company.
Detailed analysis of existing AI agents in use by a company and the potential security implications, including external AI services and MCP use.
Review of container platforms in use alongside AI and ML needs in preparation for secure, enterprise-ready OpenShift AI clusters.
Creates an AI infrastructure plan for enterprise organizations to ensure data and AI solutions are deployed cost effectively, with scale and purpose to business outcomes.
Designs one or more AI agents for cybersecurity use, ensuring proper MCP and workflow analysis with organizational privacy, governance and compliance controls in place.
Architecting and AI-ready environment using OpenShift best practices and enterprise requirements based on GPU usage, AI development processes and model use cases.
Ensures agents using MCP and AI platform interactions introduce new AI security standards to protect corporate data and AI interactions from out-of-band security implications.
Implements one or more AI agents for cybersecurity use, including connection with secure MCP and automation platforms to properly audit AI and agentic communications.
Installation and configuration of AI-ready environment using OpenShift, leveraging an OpenShift AI Platform Design engagement to properly setup a Red Hat cluster for AI use cases.
Scheduled subscription service reporting on targeted attacks, methodologies and tools using AI and data assets to review an organization’s continually evolving security posture.
Gruve operates across the full AI stack, from silicon and compute architecture to data foundations and AI agents. This allows us to design infrastructure decisions that are technically sound and commercially rational.
Gruve works closely with hyperscalers, GPU providers, AI startups, and enterprise IT vendors. We exchange signals early, before trends become defaults. That collective intelligence is built into every infrastructure decision we make.
AI infrastructure without security is a liability. Gruve embeds governance, access control, and compliance into the infrastructure layer so AI can scale without increasing risk.