On-Premise Deployment Capabilities
Enterprise AI without sacrificing data sovereignty.
Data sovereignty
On-premise or private cloud when the scope says so. The data path is agreed and verified for that deployment, including the model, voice services, integrations, and other processing.
Compliance-ready
Encryption, tenant isolation, and audit logs can be included. These controls support a customer security review. They are not a SOC 2 or GDPR certification.
Full agent capabilities
RAG, workflow automation, voice, browser automation, and integrations — all deployable on-premise.
On-Premise AI Agent Use Cases
Industries and teams that require data to stay in-house.
HR and employee data
Internal copilots for policies, benefits, and leave requests — with employee records never leaving your network.
Legal and compliance
Query contracts, regulations, and internal policies with audit-friendly citations and access controls.
Healthcare operations
Support staff with grounded answers from the clinical protocols and administrative procedures in scope. Access controls, encryption, and audit logs can be included. That does not make the deployment HIPAA compliant.
Financial services
Internal knowledge agents for trading rules, compliance procedures, and client service playbooks.
Government and public sector
Citizen-facing and internal agents deployed in government-approved environments with full audit trails.
Regulated manufacturing
SOP search, quality procedures, and safety protocols — grounded in approved documentation on your servers.
How It Works
One agreed production workflow, typically delivered in about 30 days once scope and access are confirmed. Discovery and the written scope come before that delivery period.
1. Discovery Call
We review your workflows, tools, data sources, and success criteria.
2. Solution Design
We define the agent, integrations, approval gates, and launch plan.
3. Build & Integrate
We connect your documents, APIs, and systems into a working prototype.
4. Test & Refine
Real users test the workflow. We tune prompts, rules, and reliability.
5. Launch & Expand
Deploy to production with audit logs, training, and a roadmap for the next automation.
Why Teams Choose Tyon
Custom AI agents that answer, act, and automate — not generic chatbot wrappers.
Data stays yours
On-premise and private cloud deployment with no requirement to send data to external AI vendors.
Controls you can include
Encryption, audit logs, and tenant isolation can be included in the deployment. Tyon does not certify that deployment as SOC 2 compliant.
No vendor lock-in
Provider-agnostic — switch AI models without rebuilding agents, workflows, or integrations.
Delivery after scope
One agreed production workflow is typically delivered in about 30 days once scope and access are confirmed, including on-premise deployments. Discovery and the written scope come before that delivery period.
Frequently Asked Questions
What does on-premise deployment mean?
The Tyon platform runs on servers inside your network or private cloud. Conversations, documents, and agent configurations stay within your infrastructure.
Can we use our own AI models on-premise?
Yes. Tyon supports open-source models (like Llama) running entirely on your servers, as well as cloud models accessed via your own API keys.
Is on-premise more expensive?
On-premise deployments require infrastructure investment but eliminate per-token cloud costs and address data residency requirements that cloud-only solutions cannot.
Do on-premise agents have the same features?
Yes. RAG, workflow automation, voice, browser automation, RBAC, and audit logging are all available in on-premise deployments.
How do you handle updates?
We provide update packages and deployment support. Your IT team controls when updates are applied.
Can we start in the cloud and move on-premise later?
Yes. Agent configurations, skills, and workflows transfer between deployment environments.