Private AI: Secure, Scalable AI for Business

Private AI is redefining how businesses adopt artificial intelligence by enabling them to leverage powerful models without sacrificing data privacy or regulatory compliance. While public tools like ChatGPT, Copilot, and Gemini have accelerated AI adoption, they come with one major tradeoff: your data is no longer entirely in your control.

That’s why more companies are turning to Private AI—an approach that balances performance with privacy, ownership, and control.

What is Private AI?

Private AI refers to the deployment of large language models (LLMs) and other AI tools in secure, ringfenced environments where only your organisation can access the data and models. This typically involves hosting AI on-premises or in a private cloud, and integrating safeguards such as:

• Data encryption at rest and in transit
• Role-based access controls
• Audit logs and observability tools
• Isolation from public APIs or shared infrastructure

In contrast to public AI, where input and output may be logged, shared, or reused to train models, Private AI ensures full ownership and protection of sensitive data.

Why Private AI Matters More Than Ever

Businesses today face a growing paradox: AI boosts productivity, but sharing sensitive information with external services introduces compliance and IP risks. This is especially critical in sectors like healthcare, finance, law, and government, where data breaches or mishandling can be catastrophic.

Private AI solves this dilemma by offering the same generative AI capabilities but with end-to-end data control.

Benefits of Private AI include:

• Data sovereignty: Your data never leaves your cloud environment
• Regulatory compliance: Meet SOC2, GDPR, ISO27001, APRA CPS 234, and more
• Customisability: Fine-tune models on your own data
• Security: Protect against model leaks or shadow AI use
• Performance: Deploy powerful LLMs optimised for your workload

Private AI vs Public AI: Key Differences

Feature	Private AI	Public AI
Data Control	Full control and visibility	Data may be stored, logged, or reused for training
Security	Enterprise-grade encryption and access controls	Limited by third-party platform settings
Compliance	Customisable to meet internal and regulatory requirements	Must comply with provider’s data policies
Deployment	Hosted privately (cloud or on-prem)	Hosted externally by AI provider
Costs	Higher setup, scalable over time	Low-cost entry, but usage-based costs can balloon
Ease of Use	Requires initial setup, often with managed services	Plug-and-play experience

Overcoming the Challenges of Private AI

Traditionally, building and maintaining a Private AI environment has been complex and costly. Companies needed to choose the right model, provision infrastructure, manage security, and build devops pipelines all before getting any value.

That’s where platforms like Bach come in.

Bach is a cloud management platform that makes Private AI easy. We combine the ease of public AI with the privacy and security of a private deployment. With built-in CI/CD, observability, and business-ready AI apps, Bach removes the technical burden so you can focus on results not infrastructure.

Embrace the Future with Private AI

As generative AI becomes core to modern business, companies must choose: move fast with public tools and risk privacy or adopt Private AI and scale securely.

Private AI is not just a secure alternative it’s the smart default for businesses that value control, compliance, and long-term agility.

Ready to deploy Private AI in your organisation? Talk to us and discover how to get started fast.