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Clear definitions for Redacted AI Solutions, Ralph Luketic II, Grace OS, R.A.I.S.E., air-gapped systems, governed agents, local retrieval, model capacity, risk, and the buying process.
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Redacted AI Solutions LLC is an East Lansing, Michigan AI infrastructure company founded by Ralph Luketic II. It designs private AI operating systems for organizations that need models, retrieval, data, tools, and agentic workflows to remain local, governed, reviewable, or fully disconnected from routine cloud inference.
Ralph Luketic II is the founder and AI systems architect behind Redacted AI Solutions, Grace OS, and R.A.I.S.E. Based in East Lansing, he brings more than 30 years of hands-on work with computer hardware, repair, Linux, networking, and practical systems troubleshooting to the design of private and governed AI infrastructure.
Grace OS is the orchestration and control layer for the full private AI system. It organizes durable knowledge, users, permissions, tools, models, agents, workflows, approvals, decision state, and organizational memory. Grace determines how work is routed and governed; it is not a single chatbot or model.
R.A.I.S.E. is the Redacted AI Secure Environment: the secure local kernel and runtime in which approved models, private retrieval, evidence, tools, and agent actions execute. It can be configured for on-premise or air-gapped operation without a routine external inference path.
Grace OS controls and orchestrates the whole system; R.A.I.S.E. provides the protected execution environment. Grace manages knowledge, policy, tools, agents, workflows, and decision state. R.A.I.S.E. runs the models, retrieval, evidence handling, and bounded agent actions inside the approved local infrastructure.
An air-gapped AI system runs inside an environment isolated by design, with no routine network path to external cloud inference. A responsible deployment also defines controlled procedures for software and model updates, approved data movement, removable media, backups, recovery, physical access, identity, maintenance, and incident response.
Private retrieval-augmented generation uses an organization's approved source collections to retrieve relevant evidence for a local model without sending those sources through a routine cloud inference path. Retrieval can improve grounding and source visibility, but people must still verify citations, omissions, interpretations, and professional conclusions.
A governed AI agent receives a defined role, approved evidence, permitted tools, explicit limits, policy checks, and human approval requirements before it can act. Its requests, sources, tool use, exceptions, approvals, and outcomes are designed to remain attributable and reviewable. Governance improves control; it does not make an agent infallible.
R.A.I.S.E. is model-flexible rather than tied to one vendor. A practical model can run when its license permits the use and the selected hardware provides enough memory, compute, storage, power, cooling, resilience, and operating budget. The workload determines whether the right system is an edge device, workstation, server, or GPU cluster.
No. Local execution removes a routine external inference path, but security still depends on configuration, identity, physical safeguards, supply-chain controls, approved media handling, updates, backups, maintenance, monitoring, and human behavior. Redacted AI Solutions does not represent local deployment as automatic compliance or zero risk.
Redacted AI Solutions' 45-day private AI pilot starts at $7,500 for the service scope, plus workload-fit hardware and unusual third-party licensing when required. The starting scope covers one bounded workflow, approximately 80–120 hours of typical delivery effort, governance and evaluation, documentation, and a scale, revise, or stop recommendation.
A private AI system is worth considering when an organization has a valuable workflow, an accountable owner, controlled source material, measurable pain, and a genuine reason that data or inference should remain local. Redacted AI Solutions specializes in research, edge technology, and legal systems while evaluating qualified medical, government, and enterprise private-RAG opportunities.
Your workflow will be specific
Bring the workflow, source material, authority, consequence of failure, and reason local operation matters. Do not send sensitive data through the public website.
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