Context & tools
The material the work starts from: the sources, documents and tools a team already relies on.
Enterprise Infrastructure
Your AI. Your Cloud. Your Rules.
Deploy Swfte's full AI platform — models, agents, workflows, and data pipelines — inside an isolated, dedicated cloud environment that you control. Built for organizations where compliance, security, and data sovereignty are non-negotiable.
In short:Deploy Swfte AI models, applications, and data bridges in your own dedicated cloud environment. Secure, compliant, auditable, and scalable infrastructure for regulated industries.
- Isolated VPC or bare-metal: AWS, Azure, GCP, or your data center
- Run proprietary & open-source models with full weight control
- Bridge CRM, ERP, and internal APIs with zero public internet exposure
DedicatedSingle-tenant infrastructure
<50msIntra-VPC Latency
0Data Egress
Your Dedicated Environment
AI Models
LLaMA · Mistral · GPT-4
Agent Workflows
Studio · Orchestration
Knowledge Base
RAG · Vector Search
Security Layer
RBAC · Audit · Encryption
Private Link
CRM
ERP
Data Warehouse
FedRAMP
HIPAA
SOC 2
GDPR
On-Premise
Air-Gapped
Data Residency
Multi-Region
Three Pillars of Dedicated Deployment
We bring the infrastructure expertise, AI intelligence, and application integration together as one seamless solution.
How Dedicated Cloud Works
01
Step 1
Provision Your Environment
We spin up an isolated VPC in your preferred cloud region, or deploy on bare metal within your data center. Infrastructure-as-code ensures reproducibility.
02
Step 2
Deploy Models & Agents
Bring open-source models (LLaMA, Mistral) or connect your licensed models. Build agents and workflows in Studio: everything runs inside your perimeter.
03
Step 3
Bridge Your Data
Connect knowledge bases, databases, and internal APIs via secure private links. RAG pipelines, semantic search, and vector stores all stay within your network.
04
Step 4
Operate & Scale
Full observability with tracing, metrics, and cost analytics. Auto-scale compute, manage model versions, and roll back instantly: all governed by your policies.
Purpose-Built GPU Compute
Dedicated NVIDIA accelerators with InfiniBand interconnect and automated failover. No shared tenancy, no noisy neighbors.
H100 SXM
Training and real-time inference for 70B+ parameter models
80 GB HBM3 · 3.35 TB/s
A100
Fine-tuning and batch inference for 7B–30B parameter workloads
80 GB HBM2e · 2 TB/s
L40S
High-throughput inference, RAG pipelines, and multimodal workloads
48 GB GDDR6
400 Gb/s
NDR InfiniBand
N+1
Automated Failover
K8s
GPU Scheduling
Security & Compliance Built In
Every layer of the stack is designed for regulated, high-control environments.
SOC 2 in preparation
A SOC 2 Type I audit is being prepared; the target date is on our trust page. No independent audit report exists yet.
Encryption in transit and at rest
TLS in transit and encrypted storage at rest. Customer-managed keys are scoped per engagement and are not a standard offering today.
Full Audit Trails
Model invocations, data access and configuration changes are logged and exportable for compliance reporting.
Zero-Trust Access Controls
OIDC sign-in, role-based access and per-tenant isolation. SAML SSO is in development.
SOC 2 Type I
In preparation
Single-tenant
Dedicated infrastructure
Support
Scoped per contract
Air-Gapped
Available option
Illustrative deployment scenarios
Illustrative examples of how a regulated organisation could use a dedicated environment. They are not customer case studies.
Financial Services
Illustrative: private AI for risk analysis at a bank
Illustrative scenario, not a customer: a bank moves fraud and risk analysis into a dedicated, network-isolated environment so transaction data never reaches external networks.
Read more
Healthcare & Life Sciences
Illustrative: AI for clinical research
Illustrative scenario, not a customer: a health system analyses research data in a dedicated environment. Swfte does not sign HIPAA BAAs today, so this requires a separately agreed compliance scope.
Read more
Government & Defense
Illustrative: sovereign AI with no internet connectivity
Illustrative scenario, not a customer: agents process sensitive documents on isolated infrastructure with chain-of-custody logging. Government authorisations such as FedRAMP are not held today.
Read more
Dedicated Cloud FAQ
We support AWS, Microsoft Azure, and Google Cloud Platform. We also offer bare-metal deployments in your own data centers or colocation facilities for maximum control.
Standard cloud deployments take 2-4 weeks. Bare-metal and air-gapped deployments typically require 4-8 weeks depending on hardware procurement and security review timelines.
Absolutely. Our Model Gateway supports any model: open-source (LLaMA, Mistral, Falcon), commercial (GPT-4, Claude), or your proprietary fine-tuned models. All run within your dedicated environment with unified observability.
None yet. A SOC 2 Type I audit is in preparation (target date on our trust page). We do not hold ISO 27001, HIPAA, FedRAMP, PCI DSS or HITRUST attestations. We will work with your compliance team on the controls a dedicated environment needs and state plainly what we can and cannot evidence.
Ready to Deploy AI on Your Terms?
Talk to our infrastructure team about setting up a dedicated environment tailored to your compliance, data residency, and performance requirements.
Custom enterprise plans available • See our trust page for compliance status
Connection map / Dedicated Cloud
Draw the boundary for a private deployment
Inspect three decisions for an illustrative isolated environment. Illustrative authored example · snapshot · 7 September 2026. Supplied catalogue copy, not verified performance evidence; this preview does not execute a workflow.
Request / boundary
An internal application sends a model request.
Routing consideration
Place the application endpoint and model service inside the planned private boundary.
Architecture question: which network paths must be permitted?
Request / boundary
The team wants to operate its own model weights.
Routing consideration
Separate model storage and serving responsibilities from application ownership.
Architecture question: who can update, load and retire a model?
Request / boundary
A serving instance becomes unavailable.
Routing consideration
Define recovery responsibilities before selecting an operating configuration.
Architecture question: what failover procedure will the team test?
How the pieces connect
One useful outcome.
Six deliberate layers.
A spatial explanation of the workflow.
Select a stage or scroll to explore.
EXPLORE THE ASSEMBLY
Intelligence
The reasoning step. A model reads the context that was gathered and proposes something a person can act on.
Review boundaries
The limits set before the work runs — what is in scope, what is refused, and who is asked when it is unclear.
Workflow
The sequence itself: the order of steps, the handoffs between them, and where a person is required.
Deployment
How the result reaches the people who use it, and the conditions under which it is allowed to run.
Evidence
What is kept afterwards so a reviewer can retrace the decision: inputs, choices, and the person accountable.
CONCEPTUAL WORKFLOW MODEL — NOT A DEPICTION OF SYSTEM ARCHITECTURE
Illustrative authored example · snapshot · 7 September 2026. Capabilities and figures require confirmation.