Enterprise AI you can trust.
Is your business wanting to embrace artificial intelligence but concerned about privacy and data security? With our private LLMs, you get all the power of modern generative AI, but with full visibility, control and compliance through a self-hosted AI system.
Bring advanced AI into your business, safely and confidently.
A secure AI engine, built for your business.
A private LLM (Large Language Model) is a fully controlled, self-hosted AI system that runs inside your environment rather than a public platform. It can be deployed in a secure cloud tenancy or on-premise, trained on your business data and governed by your policies. It delivers the same capabilities as modern generative AI – analysis, automation, content creation, summarisation, reasoning – but with full visibility, control and compliance.
Why develop a private LLM?
- Total control over your data: Information never leaves your environment, reducing risk and meeting strict compliance requirements.
- AI aligned to your business: Your model learns from your documents, policies, processes and domain knowledge.
- Secure innovation: Adopt AI without exposing your intellectual property or sensitive data to public models.
- Enterprise governance: Define what the model can and cannot do using audit logs, access controls and policy.
Is a private LLM right for my business?
Organisations that handle sensitive information, operate in a regulated sector (such as finance, health or legal), or simply want full ownership of their AI capability, will benefit from a private LLM. Self-hosted AI is the most strategic path for businesses that want the power of generative or agentic AI but can’t use public AI tools because of:
- Privacy obligations.
- Industry-specific compliance.
- Confidential data and IP risk.
- Security requirements.
- Regulatory audits.
Business-trained artificial intelligence delivered privately in your environment.
Public AI services offer convenience, but they can’t deliver the level of control required for enterprises managing sensitive data or complex governance. For these businesses, a private LLM becomes a critical part of AI strategy.
Strategic & operational value.
CIOs, CISOs and technology leaders use private LLMs to deliver the benefits of modern AI – automation, analysis, reasoning and workflow augmentation – while maintaining full visibility and governance across the entire AI stack.
Data control & governance.
All processing occurs inside your environment, supporting NIST, ISO27001, New Zealand Privacy Act 2020 and sector-specific requirements.
Integration with enterprise systems.
Connects to SharePoint, Teams, CRMs, ERPs, SQL databases, document libraries and other platforms via secure connectors and APIs.
Domain-specific performance.
Fine-tuned or RAG-enhanced models deliver more accurate outputs using your policies, knowledgebases and operational data.
Automation through agentic workflows.
Supports agent-based task execution, scheduled prompts, API-driven decisioning and automated document workflows.
Reduced operational load.
Streamlines manual processes such as reporting, summarisation, communication generation, data analysis and internal support.
Sovereign & auditable.
Meets strict audit, traceability and retention requirements for regulated sectors.
Our approach to strategic private LLM development.
1. Discovery & Architecture
We assess your requirements, data sources, industry standards, security policies, and use cases.
We design an AI architecture suited to your business – private cloud, hybrid or on-premise.
2. Model Selection & Environment Build
We select and configure the most suitable model (open-source or licensed) based on your needs.
We set up the secure environment, networking, identity and access controls.
3. Data Integration & Training
We index your business data from SharePoint, Teams, file systems, CRMs, knowledgebases and other sources. We apply filters so the model only uses approved and current content.
4. Governance & Safety Framework
We configure permissions, content filters, audit logging, retention, behavioural constraints and industry-specific compliance requirements.
5. Workflow Integration & Adoption Support
We provide a secure interface for staff, or integrate the LLM into existing applications, and support your team to integrate AI into daily work.
6. Ongoing Management
We maintain, update, monitor and optimise your private LLM to ensure ongoing performance, accuracy and security.
Frequently asked questions.
Why can’t we just use ChatGPT, Copilot or Azure OpenAI?
Public AI tools are powerful but pose challenges for privacy, regulation, IP protection and data residency. A private LLM keeps all data inside your environment. Azure OpenAI is secure but still relies on Microsoft-managed infrastructure and shared model weights.
What industries benefit most from private LLMs?
Healthcare, pharmaceuticals, legal, finance, local government, engineering, manufacturing and any organisation with high compliance or confidential information.
Where is the model hosted?
You choose: your cloud tenancy (Azure, AWS), a private infrastructure environment, or on-premise servers.
Can we restrict what staff can ask or access?
Yes. Access is controlled through your identity systems, and governance rules define what the model can do.
Can a private LLM be trained on our files ?
Yes. The model uses only the data sources you approve – SharePoint, Teams, file servers, CRMs and more.
Can a private LLM enforce zero-trust security requirements?
Yes. We integrate with Entra ID, conditional access, RBAC and network restrictions.
Why Podcom?
Podcom helps enterprise technology leaders deploy AI securely and strategically, with full operational control. Speak with our team to plan your private LLM architecture and deployment. Our approach is transparent, practical and focused on outcomes.
Local experts who will learn your business needs.
Deep expertise in secure cloud environments.
Tailored AI solutions designed for your needs.
End-to-end delivery – from strategy to support.