HiveAI On-Premises: Your AI agents. Your infrastructure.
Sensitive data should not hold your AI ambitions back. With HiveAI On-Premises, you can run AI agents and language models within your own infrastructure, helping your people work with information that needs to stay in your organisation.
When your data needs to stay with you
Put sensitive information to work, within your boundaries
Some information needs a tightly controlled environment. Patient records, confidential research, financial information and critical infrastructure documentation can all create specific requirements for how and where AI is used.
HiveAI can be deployed in your own data centre, with locally hosted models processing information within your environment. It also supports fully isolated environments without an internet connection.
Your people can use AI to find information, summarise documents and support everyday work while keeping processing within the boundaries you define.
What is on-premises AI?
On-premises AI means running AI models on infrastructure within your organisation rather than sending requests to an external model service.
But a model alone does not give your people a working solution. It also needs a way to connect with users, access approved information and carry out tasks.
HiveAI brings these parts together. It connects locally hosted models, agents and your internal systems, giving you a foundation for building and managing your digital workforce.
1. Keep control of your data
Process information within your environment
Prompts, documents and model responses can remain on infrastructure you control. You decide what agents can access, how information is handled and where it is stored.
This supports organisations with strict confidentiality, data residency or isolation requirements.
2. Plan capacity around your needs
Run models on your own hardware
Locally hosted models reduce reliance on usage-based fees from external model services. Instead, you plan for the infrastructure, capacity and operational support your agents need.
As usage grows, we help you assess performance and capacity so your setup continues to serve your people.
3. Choose models that fit the work
Build flexibility into your AI foundation
HiveAI supports locally hosted models, giving you more choice over the technology behind your agents.
We help you select and evaluate models against your use cases, balancing response quality, speed and hardware requirements. Supported models can be changed through configuration, reducing the need to rebuild the surrounding solution.
On-premises, cloud or a combination?
Choose the environment around the work
The right deployment depends on your data requirements, the capabilities your agents need and how you want to operate the solution. HiveAI supports models in your data centre, your cloud tenant or a combination, selected by agent.
Consideration |
On-premises |
Cloud |
|---|---|---|
|
Where models run |
Within your own infrastructure |
In a cloud environment |
|
Data processing |
Can remain entirely within your local environment |
Follows the selected service’s configuration and terms |
|
Model choice |
Models suitable for local hosting and available hardware |
Models available through the selected cloud services |
|
Capacity |
Planned around your hardware and operational setup |
Scaled through cloud services |
|
Costs |
Infrastructure, energy, maintenance and support |
Service, infrastructure and usage-based costs |
|
Best fit |
Work requiring local processing or isolated environments |
Work suited to cloud processing and service-based scaling |
Healthcare
More time for care. AI within your control.
From patient administration to coordinating care workflows, healthcare teams handle work that involves highly sensitive information. AI agents can help reduce routine tasks and support professionals in their everyday work.
With HiveAI On-Premises, agents can work with approved data and systems within your own infrastructure, with defined access and human oversight. Sensitive information stays within your environment, while clinical decisions remain with your professionals.
Financial services
More time for customers. Control over sensitive information.
From customer onboarding to document processing and internal workflows, AI agents can help financial services teams move work forward and reduce manual effort.
With HiveAI On-Premises, agents operate within your own infrastructure, with clear permissions and approval steps. Your teams can put AI to work while keeping sensitive customer and business information within your controlled environment.
Research and manufacturing
More room for innovation. Control over your expertise.
From supporting research to coordinating production workflows, AI agents can help teams analyse information, automate routine tasks and take action across approved systems.
With HiveAI On-Premises, agents work within your own infrastructure, keeping confidential research, product designs and operational information in your environment. You define what they can access and do, and where human approval is required.
Critical infrastructure and defence
Support for critical work. Within your security boundaries.
From maintenance planning to operational administration, AI agents can help teams coordinate tasks, process information and support workflows involving restricted data.
With HiveAI On-Premises, agents can operate within your own infrastructure, including fully isolated networks without an internet connection. Defined permissions and human oversight keep their actions within your operational and security boundaries.
Governance and security stay part of the work
Hosting AI locally gives you control over where processing happens. Access, oversight and responsible use still need clear ownership.
We help you define what each agent can do, which information it can access, where human approval is needed and how its performance is monitored.
The HiveAI Agent Lifecycle provides a structured approach to managing agents from the first idea through development, operation and retirement.
Build your digital workforce within your boundaries
You know where your information needs to stay. Let’s explore what your people could do with it.
In a discovery session, we review your use cases, data requirements and infrastructure to identify a practical starting point for HiveAI On-Premises.