Ensure Full Control & Security with On-Prem Hardware
At LLM.co, we specialize in on-premise LLM deployments—giving you the ability to run powerful large language models entirely within your own infrastructure. No cloud dependencies. No third-party data sharing. Just AI built for privacy, performance, and precision.
Our on-prem solutions are ideal for organizations in legal, finance, healthcare, government, defense, and other sectors where control and compliance are non-negotiable.
Use The Best Open Source LLMs for Your Private, On-Prem LLM Deployment
Why On-Prem AI?
Choosing an on-premise deployment for your large language model isn't just a technical decision—it's a strategic one. When you run your own private LLM stack on your infrastructure, you gain unmatched control, security, and predictability that cloud-based solutions simply can't offer.
Complete Data Sovereignty
Every document, prompt, file, and interaction stays fully contained within your environment. Your sensitive data never touches third-party APIs, cloud endpoints, or vendor-controlled logs. This is critical for organizations where intellectual property, client confidentiality, or national security are central concerns. You own the model. You own the data. You own the outcome.
Offline Capability
On-prem deployments can operate completely offline, with no internet dependency. This is especially vital for air-gapped systems, secure facilities, disaster recovery planning, or remote field operations where reliable connectivity isn’t guaranteed—or where cloud usage is strictly prohibited.
Compliance Alignment
With on-prem AI, you don’t have to ask whether your deployment meets GDPR, HIPAA, or SOC 2—you architect it to comply by design. Our systems are configurable to align with your existing security policies, audit requirements, encryption standards, and identity access management (IAM) protocols. You stay compliant because you stay in control.
What's Included in Our On-Prem AI Solutions
At LLM.co, our on-premise deployments are built to deliver private, performant, and production-ready AI. Each implementation is tailored to your infrastructure, use case, and compliance requirements.
Custom-Tuned LLMs Trained on Your Data
We deploy large language models that are either fine-tuned on your proprietary content—contracts, policies, manuals, chat transcripts, etc.—or preloaded with best-in-class open-source models like LLaMA, Mistral, Mixtral, Phi, or Falcon. This allows your AI to speak your organization’s language and deliver domain-specific accuracy out of the box.
Containerized AI Infrastructure
All deployments are fully containerized using Docker or Kubernetes, allowing for portability, scalability, and security. Whether you're deploying on bare metal, a secure private cloud, or a virtualized on-prem environment, our architecture is optimized for ease of maintenance, controlled updates, and infrastructure-as-code integration.
Integrated RAG Pipelines
We implement Retrieval-Augmented Generation (RAG) pipelines that allow your LLM to pull real-time context from internal documents, databases, and knowledge bases before responding. This dramatically improves accuracy while keeping your system lightweight—ideal for document review, internal search, compliance checks, or SOP guidance.
Unique Features, Literally "Out-of-the-Box"
Every deployment includes robust role-based access control (RBAC) to restrict who can query, manage, and update the system. Data is encrypted in transit and at rest, and comprehensive audit logging ensures traceability for every request and user action—essential for regulated environments and internal governance.
Email/Call/Meeting Summarization
LLM.co enables secure, AI-powered summarization and semantic search across emails, calls, and meeting transcripts—delivering actionable insights without exposing sensitive communications to public AI tools. Deployed on-prem or in your VPC, our platform helps teams extract key takeaways, action items, and context across conversations, all with full traceability and compliance.
Security-first AI Agents
LLM.co delivers private, secure AI agents designed to operate entirely within your infrastructure—on-premise or in a VPC—without exposing sensitive data to public APIs. Each agent is domain-tuned, role-restricted, and fully auditable, enabling safe automation of high-trust tasks in finance, healthcare, law, government, and enterprise IT.
Internal Search
LLM.co delivers private, AI-powered internal search across your documents, emails, knowledge bases, and databases—fully deployed on-premise or in your virtual private cloud. With natural language queries, semantic search, and retrieval-augmented answers grounded in your own data, your team can instantly access critical knowledge without compromising security, compliance, or access control.
Multi-document Q&A
LLM.co enables private, AI-powered question answering across thousands of internal documents—delivering grounded, cited responses from your own data sources. Whether you're working with contracts, research, policies, or technical docs, our system gives you accurate, secure answers in seconds, with zero exposure to third-party AI services.
Custom Chatbots
LLM.co enables fully private, domain-specific AI chatbots trained on your internal documents, support data, and brand voice—deployed securely on-premise or in your VPC. Whether for internal teams or customer-facing portals, our chatbots deliver accurate, on-brand responses using retrieval-augmented generation, role-based access, and full control over tone, behavior, and data exposure.
Offline AI Agents
LLM.co’s Offline AI Agents bring the power of secure, domain-tuned language models to fully air-gapped environments—no internet, no cloud, and no data leakage. Designed for defense, healthcare, finance, and other highly regulated sectors, these agents run autonomously on local hardware, enabling intelligent document analysis and task automation entirely within your infrastructure.
Knowledge Base Assistants
LLM.co’s Knowledge Base Assistants turn your internal documentation—wikis, SOPs, PDFs, and more—into secure, AI-powered tools your team can query in real time. Deployed privately and trained on your own data, these assistants provide accurate, contextual answers with full source traceability, helping teams work faster without sacrificing compliance or control.
Contract Review
LLM.co delivers private, AI-powered contract review tools that help legal, procurement, and deal teams analyze, summarize, and compare contracts at scale—entirely within your infrastructure. With clause-level extraction, risk flagging, and retrieval-augmented summaries, our platform accelerates legal workflows without compromising data security, compliance, or precision.
How Our On-Prem AI & LLM Process Works
Our on-premise LLM deployments are fully managed and customized to fit your infrastructure, security posture, and business needs. From first conversation to post-deployment support, here’s how we deliver AI that works within your walls—and on your terms.
Discovery & Planning
We begin by conducting a deep-dive discovery session with your stakeholders—technical, legal, and operational—to understand your infrastructure, data governance requirements, use cases, and AI goals.
Whether you're focused on document summarization, legal drafting, internal knowledge retrieval, or multi-agent workflows, we tailor the scope and architecture to match your environment. We’ll also evaluate whether a cloudless air-gapped deployment, a VPC-based hybrid, or a local hardware solution is the best fit.
Deliverables: Solution architecture, risk assessment, deployment strategy, compliance alignment
Installation & Integration
Next, we provision and install the LLM stack—containerized using Docker or Kubernetes—directly into your infrastructure (or onto your LLM-in-a-Box hardware). We connect your model to internal data sources such as file servers, document management systems, or databases, depending on your use case.
We also integrate vector databases and RAG pipelines, enabling real-time document retrieval and context-aware responses, as well as build connectors to tools like SharePoint, Salesforce, Confluence, or custom repositories as needed.
Deliverables: Installed private LLM system, connected data pipelines, initial inference-ready deployment
Fine-Tuning & Customization
We customize the model to your business. That can include embedding your proprietary knowledge base, creating structured embeddings for key documents, tuning the model using instruction-based prompts, or applying light fine-tuning with domain-specific datasets.
We’ll also configure your preferred interface—whether it’s a web chat, search bar, API, Slack bot, or integration with internal tools—ensuring your users interact naturally with the LLM in your organization’s voice and context.
Deliverables: Custom LLM logic, document embeddings, interface layer, prompt strategy
User Access & Governance
Security and governance are top priorities. We implement role-based access control (RBAC) to ensure only authorized users can interact with or administer the system. We configure encryption, usage logging, audit trails, rate limits, and token quotas, all in alignment with your internal IT and compliance frameworks.
We also help you define model routing rules, fallback protocols (for hybrid setups), and provide documentation and training for both admins and end users.
Deliverables: Governance policies, access control setup, monitoring configuration, usage documentation
Private LLM Blog
Follow our Agentic AI blog for the latest trends in private LLM set-up & governance
FAQs
Frequently Asked Questions (FAQs) About On-Prem Private LLM Deployments
Our deployments are flexible. For lightweight models (e.g. 7B parameters), a modern CPU or mid-tier GPU server will suffice. For larger models (13B–70B+), we recommend systems with high-core CPUs, NVIDIA GPUs (A100, H100, or RTX-class), 128GB+ RAM, and fast NVMe storage. We also offer preconfigured LLM-in-a-Box hardware options if you don’t already have infrastructure in place.
Yes. Our on-prem LLMs are designed to run in air-gapped environments with no internet access required. Once deployed, the system is fully self-contained, including vector databases, retrieval pipelines, UI layers, and administrative tools. No cloud access is ever required unless you explicitly request hybrid capabilities.
We support a variety of pre-trained open models including LLaMA, Mistral, Mixtral, Falcon, Phi, and others. Depending on your needs (context length, performance, licensing), we help you select the most suitable model. We can also integrate custom fine-tuned models or those you’ve trained in-house.
Yes. We support multiple forms of customization, including prompt tuning, embedding generation, and instruction-based fine-tuning. We help you build a model that understands your specific language, terminology, workflows, and document structures. Training is done securely—either on-site or within your VPC—with no external data exposure.
An on-prem deployment runs entirely within your infrastructure—fully private, air-gapped if needed, and with no external model calls. A hybrid deployment still prioritizes privacy but allows you to optionally route certain queries to public models (like GPT-4 or Claude) via secure gateways for more complex reasoning or larger context windows. You choose where your data goes.
Yes. Our systems are built to support compliance from the ground up. Because everything runs locally, you retain full control over data residency, retention, and access policies. We’ll work with your legal and IT teams to align deployments with your specific regulatory requirements.
Absolutely. Our architecture is designed to integrate with SharePoint, Confluence, document management systems, file servers, custom CRMs, and more. We also offer API access, private chat interfaces, and the ability to embed LLM functionality into your internal tools and workflows.
We offer ongoing support plans that include troubleshooting, model updates, security patches, retraining, and system audits. Enterprise clients receive access to a dedicated account manager and SLA-backed response times. You can also opt for self-managed deployments with as-needed support.
Yes. For large enterprises with multiple facilities or jurisdictions, we can configure distributed deployments, including syncing models across secure regions, federated data indexing, or location-based inference rules. We design for scalability and governance across your entire operation.
Depending on complexity, most standard deployments take 2–6 weeks from kickoff to production. Simpler proof-of-concept systems can go live in as little as 1–2 weeks. Larger enterprise rollouts with custom integrations or compliance reviews may take longer.