On-Premise SLM Deployment for the Enterprise
Your data. Your model.
Large language models process your queries on external servers, exposing confidential documents, proprietary workflows, and sensitive client data to third-party infrastructure beyond your control. For many, this is an unacceptable risk. We build compact, domain-specific fine-tuned SLMs that run entirely within your own infrastructure; a fully air-gapped, private SLM deployment with no external API calls and no data leaving your perimeter.
On Premise
Runs natively on your servers as a fully air-gapped deployment. No data ever leaves your network.
Cheaper
Fixed-cost AI: no per-token billing. Unlimited inference at a fixed infrastructure cost.
Private
A true private SLM — your documents and workflows never touch a third-party server.
Domain Accuracy
A domain-specific fine-tuned SLM outperforms generalist models on your actual workflows.
On-premise SLM vs. API LLM
A general-purpose API model and a domain-specific SLM deployed on your infrastructure solve the same problem in very different ways. Here's how they compare.
On-Premise SLM
API LLM
Data privacy
Stays entirely within your infrastructure, nothing leaves your perimeter.
Every query is sent to a third-party server outside your control.
Cost model
Fixed infrastructure cost. No per-token billing, no usage ceiling.
Per-token pricing that scales directly with usage and headcount.
Latency
Local inference, no round-trip to an external API.
Dependent on external network conditions and provider load.
Domain accuracy
Fine-tuned on your documents, logic, and terminology.
Generalist model with no visibility into your specific domain.
Compliance & audit
Full control over data residency, retention, and audit trails.
Governed by the provider’s terms, retention policy, and jurisdiction.
What we do
We proceed from scoping to on-premise deployment in three steps. You receive a domain-specific fine-tuned SLM that runs entirely on your own infrastructure.
Use Case Definition
We scope exactly what the model needs to do, which tasks, decisions, and domain logic it must master.
Fine-Tuning
We extract and produce the necessary data from your documents and workflows, then train a domain-specific SLM on your specific logic and needs.
On-Premise Deployment & Licensing
We deploy the appropriate infrastructure inside your environment, fully air-gapped, and transfer the model under a commercial license.
Model Delivered
Domain-aligned, privately deployed, fully owned. No vendor dependency. No per-token cost.
Curious what a domain-specific SLM would look like for your workflows?
Book a Scoping CallFrequently asked questions
A system prompt only steers a general-purpose model at inference time, the underlying model still runs on external servers and still requires an API call per query. A fine-tuned, on-premise SLM is trained directly on your domain data and deployed entirely inside your infrastructure, so no query or document ever leaves your network.
Requirements depend on model size and expected load, and we scope this with you during Use Case Definition. Because we build compact, domain-tuned SLMs rather than general-purpose LLMs, most deployments run on far less hardware than a comparable large-model setup.
Most engagements move from scoping to a deployed, licensed model in a matter of weeks, not months, since fine-tuning targets a specific use case rather than general capability.
Yes. The model is transferred to you under a commercial license at deployment. There is no ongoing per-token fee and no dependency on us or any external vendor to keep running it.
We scope a refresh cadence with you based on how often your underlying documents and workflows change. Updating a domain-tuned SLM is a targeted fine-tuning pass, not a full retrain.
Ready to own your model?
Book a 30-minute scoping call. We'll assess your use case and outline a realistic on-premise deployment plan.