Your organisation already has a way to secure enterprise applications. You decide which networks can reach them, who can sign in, and which external services they can contact. Adopting AI should not require abandoning that approach.
We deploy Pristan.chat in your cloud environment, where your team controls network access just as it does for your other applications. Employees get an AI workspace; IT keeps control of the infrastructure and connectivity.
Your cloud. Your network. Your rules.
Keep Pristan on private networks, require your corporate VPN, restrict incoming connections, and apply your own firewall and outbound-access rules. The platform does not need to be publicly accessible.
Your infrastructure team manages these controls through the cloud and network tools it already uses. Pristan runs within that environment as an enterprise application, subject to your deployment standards, monitoring, and operational policies.
The same principle applies to a compatible deployment on private infrastructure. Your organisation chooses the environment and access boundary rather than accepting a public application as the only way to use AI.
A useful workspace inside that boundary.
A model endpoint alone does not give employees a place to work. They need approved agents, conversations, projects, files, and organisational knowledge in a consistent interface.
Pristan provides an enterprise AI agent catalog and governed chat workspace. Define each agent's purpose and ownership, connect a supported endpoint, and make it available to the people who should use it. Provider accounts and API keys remain customer-managed under the BYOK approach.
For a procurement team reviewing a supplier assessment, that means working with an approved agent rather than pasting business information into an unmanaged service. The user can request a risk summary and decision brief while the organisation applies its configured access and data-protection policies.
Enterprise network controls meet AI governance.
Network access answers who can reach the application. Pristan's application-level controls address what authorised users can do once they are inside. For supported interactions, enabled policies and integrations provide:
- Catalog and ownership: a reviewable record of approved agents, their purpose, and their owners.
- Access controls: roles, groups, entitlements, and access-request workflows.
- Data protection: configurable DLP inspection and policy actions on supported content.
- Audit evidence: records of access, activity, and policy decisions for operational review.
- Usage and cost visibility: attribution across users, teams, agents, providers, and models.
Your firewall does not replace AI interaction policies, and AI interaction policies do not replace your firewall. They protect different parts of the same workflow. Pristan's controls apply to supported interactions it handles; they do not govern a provider's internal runtime or activity that bypasses the platform.
You choose where the models run.
Hosting Pristan and hosting a model are separate decisions. You can connect the workspace to an approved external model provider through an outbound connection permitted by your network rules. The model provider then processes those requests under its own service and data-handling terms.
Alternatively, connect a compatible self-hosted model within your environment. That can keep inference within your infrastructure, subject to the model's licence, available compute, endpoint compatibility, and the configuration of other enabled services.
Mistral can be one model option in this architecture. The same deployment principles apply to other supported providers and compatible self-hosted endpoints. Model origin does not determine who controls access to your Pristan deployment.
Account for every enabled AI service.
The model answering a chat is not necessarily the only model involved. Pristan separates these roles:
- The chat agent: the model used for the user's task, with its configured context and supported tools.
- ExperienceAI: the optional response-enhancement layer that can turn suitable answers into richer artifacts and visual presentations when enabled for the agent.
- Platform AI: models used by enabled AI-assisted platform features, configured separately from the conversational agent.
Each role has its own inference path. Embeddings, document processing, external tools, storage, backups, and logs also belong in your deployment review. Configure each enabled dependency to match your network and data-handling requirements, including any failover routes.
Keeping all processing inside your environment requires all relevant services to stay within that boundary. Self-hosting the workspace alone does not make an external API private. This does not change your control over access to Pristan itself.
Show the task, the policy, and the evidence.
A useful demonstration starts with a business task: submit a synthetic supplier assessment, ask an approved agent for a decision brief, and show how ExperienceAI can present the result. Then trigger a deliberate policy event and inspect its audit record.
The deployment view should show where Pristan runs and which model endpoints it contacts. If Mistral is used for chat, ExperienceAI, and Platform AI, demonstrate an actual invocation of each enabled role rather than relying on a settings screen. Compatibility and execution must be verified for the chosen models.
AI does not need to be a security exception.
Deploy Pristan in your cloud, control its network access, and make approved AI available through a workspace your organisation manages. Choose model services that fit your requirements, whether externally provided or hosted within your environment.
Give people a useful AI workspace under the same network guardrails as your other enterprise applications.
Explore Pristan in your environment
Book a live session to discuss deployment in your cloud, network access, and model options, or explore Pristan in a dedicated demo workspace.