On-premise, fine-tuned models, and AI consulting
Your infrastructure, your models, your data boundary
Dialogist Enterprise is the full platform deployed inside your own environment. Nothing leaves your network that you decide should not, and the voice and knowledge engines can be fine-tuned on your own recordings and documents.
Alongside the deployment come the people: AI and ML consultants who design the conversation model with your team, fine-tune against your domain, and stay through the rollout. For organisations where the model is the product, that is the part that matters.
Capabilities
Items marked planned or roadmap are not available today. Everything else ships now.
On-premise deployment
The complete platform — control layer, voice engine and knowledge engine — running inside your infrastructure, behind your network boundary and under your change-management process.
Model fine-tuning on your data
The voice and knowledge engines are fine-tuned on your own recordings, call transcripts and documents, so the robot understands your terminology, your products and the way your customers actually speak.
AI and ML consulting
Conversation design, evaluation sets, prompt and model strategy, and deployment planning, worked through with your team rather than handed over as documentation. We define the metrics that tell you whether it is working.
Fully isolated instances
A dedicated environment per organisation, logically and operationally separated from every other customer, for organisations whose requirements do not permit shared infrastructure.
Regional data residency
For markets that require data to stay in-country, Dialogist is deployed as an independent regional instance with its own voice and knowledge engines, storage and payment configuration.
Volumes beyond 100 concurrent calls
The self-serve product tops out at 100 simultaneous calls per robot. Above that, capacity is an enterprise engagement with its own pricing and architecture.
Enterprise SSO with SAML
PlannedSingle sign-on against your own identity provider, alongside the Google and Apple sign-in and optional two-factor authentication available on the standard platform.
Automatic dedicated environment per organisation
PlannedA fully isolated deployment provisioned automatically rather than as a services engagement.
Questions
What does 'on-premise' actually include?
The control layer, the real-time voice engine and the knowledge engine, all deployed in your environment. You keep operational control; we continue to maintain and update the platform.
Can the models be trained on our own data?
Yes. The voice and knowledge engines are fine-tuned on your recordings, transcripts and documents. Because it runs inside your environment, that data does not leave your infrastructure.
Do you hold security certifications?
The architecture is designed to support them, and we will not claim any certification on this website until it is actually obtained. Ask us directly for the current position.
How does pricing work at this level?
It is scoped per engagement rather than sold as a published list price, because it depends on deployment shape, volume, fine-tuning scope and the consulting involved. Contact us.
Who does the AI and ML consulting?
Dialogist's own data science and conversation design team, working with yours. We are not reselling a third-party model and we do not hand the work over to a partner.