mimik collaborates with Intel Corporation (Nasdaq: INTC) to bring its device-first agentic AI software infrastructure to Intel-powered AI PCs, as enterprises increasingly seek to run artificial intelligence workloads locally rather than relying solely on cloud-based infrastructure.
The collaboration will optimise mimik’s mimOE (Agentix Operating Engine) for AI PCs powered by Intel processors, enabling enterprise AI agents to execute, communicate and operate securely across client devices while maintaining governance, security and observability typically associated with cloud environments.
The companies said the initiative is designed to address a growing challenge for enterprise IT departments as AI agents become embedded in workplace applications, including browsers, email clients and development tools. While these agents are increasingly capable of carrying out tasks autonomously, many operate outside traditional enterprise management frameworks, creating new governance and security challenges.
With mimOE, Intel-powered AI PCs can function as infrastructure nodes capable of running agentic AI workloads directly on the device, across multiple devices and through gateways and data centres without requiring continuous cloud connectivity. The approach is intended to reduce cloud dependency while enabling enterprises to retain greater control over AI operations and associated costs.
Unlike conventional AI deployments that rely on centralised orchestration, mimOE distributes AI execution across endpoints while incorporating built-in zero-trust security and automated configuration. The platform also supports interoperability through open application programming interfaces (APIs) and ecosystem standards, including the Model Context Protocol (MCP), allowing AI agents to connect with both legacy enterprise applications and emerging AI services.
According to the companies, the operating engine extends cloud-like management capabilities to endpoint devices by assigning every AI agent its own verifiable identity, separate from the user operating the device. Authorisation decisions are evaluated in real time based on context, while agent activity is continuously streamed into existing enterprise security and observability platforms.
The platform also separates personal and enterprise AI environments on the same device, allowing organisations to apply governance policies without interfering with personal workloads.
As part of the collaboration, AI inference running on Intel-powered systems will be optimised using Intel’s OpenVINO toolkit, enabling workloads to take advantage of Intel’s AI acceleration capabilities while automatically routing tasks across devices, gateways and cloud infrastructure where appropriate.
The companies said enterprises will be able to deploy, test and scale agentic AI applications using existing Intel AI PC hardware, eliminating the need for significant new infrastructure investments.
“Intel-powered AI PCs offer enormous compute capability. With mimOE, that compute becomes resilient infrastructure,” said Sam Armani, Senior Vice President of Business Development at mimik.
“The real shift is the seamless fabric, where every Intel AI PC works well alone, well with peers, and well across gateways and data centers as one continuum,” he said.
Armani added that software architecture is evolving alongside advances in AI, requiring new operating models capable of supporting autonomous AI systems across enterprise environments.
Intel said the collaboration aligns with its strategy of enabling AI workloads across client devices, edge systems, data centres and cloud infrastructure.
“From AI PCs to the edge, data center, and cloud, Intel helps to power today’s enterprise,” said Dennis Luo, Senior Director and General Manager of Worldwide Developer Relations & Innovation at Intel.
He said mimik provides enterprises with a platform to discover, route and govern agentic AI workloads while OpenVINO optimises AI performance on Intel-powered AI PCs.
According to Intel, running AI workloads closer to where data is generated can reduce latency, improve privacy and lower cloud infrastructure costs by minimising the need to transfer workloads to remote computing environments.
The collaboration comes as enterprise AI adoption increasingly shifts toward hybrid deployment models that combine cloud computing with on-device AI processing. Advances in AI PCs equipped with dedicated neural processing units (NPUs) have enabled a wider range of AI inference workloads to execute locally, reducing dependence on cloud resources for routine tasks.
Industry observers expect device-first AI architectures to gain momentum as organisations seek to balance performance, data sovereignty and operational costs while deploying generative and agentic AI applications at scale.
The companies said the collaboration is intended to deliver benefits across multiple enterprise functions. Business leaders can expand AI deployments using existing PC investments, while finance teams may reduce recurring cloud expenditure by utilising client hardware already included in enterprise refresh cycles. Technology teams gain a unified operating framework capable of managing AI agents across devices, and developers can test and refine agentic AI applications locally before enterprise-wide deployment.
